Miracle-dz/UniFAR-FTUs huggingface dataset:
Back-side-illuminated image sensor with burst capturing speed of 5.2 Tpixel per second

We have developed a back-side-illuminated image sensor with a burst capturing speed of 5.2 Tpixels per second. Its sensitivity was 252 V/lux·s (12.7 times that of a front-side-illuminated image sensor) in an evaluation. Sensitivity of a camera system was 2,000 lux F90. The increased sensitivity resulted from optical and time aperture ratios of 100% and also by increasing from a higher optical utilization ratio. The ultrahigh-speed shooting resulted from the use of in-situ storage image sensor. Reducing the wiring resistance and dividing the image area into eight blocks increased the maximum frame rate to 16.7 million frames per second. The total pixel count was 760 horizontally and 411 vertically. The product of the pixel count and maximum frame rate is often used as a figure of merit for high-speed imaging devices, and in this case, 312,360 multiplied by 16.7 million yields 5.2 Tpixels per second. The burst capturing speed is thus 5.2 Tpixels per second, which is the highest speed achieved in high-speed imaging devices to date.
Measurement of actual evapotranspiration in a páramo ecosystem using portable closed chambers: Comparison between giant rosettes, tussock grasses and shrubs

The páramos are Neotropical alpine tundra‐like ecosystems that play a crucial role as biodiversity hotspots and also act as water sources for the inter‐Andean regions and cities. Improving our understanding of hydrological processes, here evapotranspiration, is crucial, especially in the context of global changes. In páramos, most research have focused on estimating potential evapotranspiration (ETo) using the Penman–Monteith method. Only a few studies have quantified actual evapotranspiration using mostly the Eddy covariance method (EC) or volumetric lysimeters. Importantly, these studies focused only on tussock grass communities, and none have addressed the effect of other plant communities specific to páramos on the actual evapotranspiration of this ecosystem. In this research, portable closed chambers were installed for the first time in a páramo (in Los Nevados National Park, between 3900 and 4100 masl) to quantify actual evapotranspration (ETa) in March and May 2019 in three representative plant communities of the páramo (giant rosettes, shrubs and tussock grasses). The ETa rates measured were then compared with ETo estimated using the Penman–Monteith method. Also, environmental factors of solar radiation, temperature and relative humidity were recorded and their influence on ETa variation was analysed. Our results indicate that ETa daily rates were very low with a high daily variation (0.290 ± 0.266 mm day−1). The shrubs showed higher ETa rates even though differences among communities were not significant. ETo rates calculated via the Penman–Monteith method were significantly higher (1.017 ± 0.468 mm day−1) than those measured using the portable chambers. Portable closed chamber is a promising method to assess ETa at small spatial and time scales and under controlled environment; however, they should be improved to enable ETa measurements on longer time periods. This study confirms the highly variable and low evapotranspiration rate of the páramo vegetation, here confirmed across different plant communities and underlines the importance of solar radiation and temperature, which were positively correlated with evapotranspiration rates.
Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda

The implementation of autonomous delivery solutions in last-mile logistics operations is considered promising. Autonomous delivery solutions can help in tackling urban challenges related to last-mile logistics operations. Urbanization creates higher mobility and transportation demand, which contributes to increased congestion levels, traffic, air pollution, and accident rates. Moreover, mega-trends, such as e-commerce, demand that logistics companies react to increased customer expectations in terms of delivery time and service. Concerning service, electrified autonomous delivery solutions have the potential to operate 24/7 and can help to overcome driver shortages. This paper conducts a systematic literature review. Based on the literature set, a snowballing procedure was applied. Complementary gray literature was included. This work discusses different autonomous delivery solutions such as Autonomous Delivery Robots (ADRs), Unmanned Aerial Vehicles (UAVs), two- or multi-tiered systems, and the concept of passenger and freight integration. The work presents advantages and disadvantages, enabling the comparison of solutions. Furthermore, a research agenda is provided, from which practical-managerial and theoretical implications can be derived. The research agenda can help researchers, manufacturers, businesses, and governmental institutions to prepare for the arrival and subsequent implementation of autonomous delivery services. Various implications related to energy demand, legislation, implementation strategy, training, and risk and safety are presented. The outcome of this work calls for collaboration among various stakeholders, encourages mutual learning, and hints at the importance of national and international development projects.
Anti-Dengue Activity of Lipophilic Fraction of Ocimum basilicum L. Stem

Ocimum basilicum L. is used to cure many types of fever in traditional medicine. This study aims to explore the antiviral activity of the lipophilic fraction of the stem of O. basilicum (LFOB) against dengue virus (DENV) and chikungunya virus (CHIKV). The LFOB was analyzed using GC-FID and GC-MS. The antiviral activity of LFOB was studied using the Vero CCL-81 cell line. The cytotoxicity assay was performed using 3-(4,5-dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT). In vitro antiviral activity and FFU assay were used to determine and confirm antiviral activity against DENV and CHIKV. Twenty-six compounds were identified in LFOB using GC/MS. The most abundant compounds were β-sitosterol (22.9%), stigmasterol (18.7%), and campesterol (12.9%). Significant reduction in DENV titre was observed under pre- and post-infection treatment conditions at a concentration of 3.125 µg/mL, but no anti-CHIKV activity was observed. Our earlier and the present AutoDock-Vina-based in silico docking study revealed that β-sitosterol and stigmasterol could form strong interactions with the DENV E glycoprotein and DENV RdRp domain, respectively. Our findings suggest that LFOB can inhibit DENV infection and might act as a potent prophylactic/therapeutic agent against DENV-2. In silico results suggested that β-sitosterol and stigmasterol may block the viral entry by inhibiting the fusion process and viral replication respectively.
LSTM Neural Network for Parkinson’s Disease Analysis

Parkinson’s disease (PD) is a brain disorder and results in involuntary or uncontrollable movements, such as stiffening, tremors, and difficulty with balance and coordination; After Alzheimer’s, Parkinson’s disease is the most common disease. Symptoms start gradually and get worse as the disease progresses. A person may experience difficulty in speaking and walking, behavioral and mental changes, sleep disturbances, tiredness, and depression. The most noticeable symptoms of the disease appear when nerve cells in a specific part of the brain weaken or die. This part of the brain is responsible for movement, and neurons produce an essential brain chemical known as dopamine, which is required to control movement in the human body. Deep learning can detect and predict various diseases, which have a significant impact on health care. This research aims to investigate the predictive capabilities of deep learning in diagnosing Parkinson’s disease, and the use of deep model is based on long-term memory (LSTM) in diagnosing disease based on a group, the data, and training. The model was conducted to prove its effectiveness, in addition to comparing it with traditional machine learning techniques where the results obtained showed that the accuracy of the LSTM model reaches 99 percent. which indicates its effectiveness in diagnosing Parkinson’s disease.
Spontaneous interparticle percolation

A study is made of the spontaneous percolation occurring when particles fall under gravity through a fixed bed of larger particles. A variety of different circumstances arise in practical applications in for example powder mixing but there are two limiting cases which are still both important. The first is when small particles cascade almost elastically through an ensemble of layer particles. It is shown that the percolation velocity is proportional to (1 – α)1/4, where α is the coefficient of restitution.The diffusion tensor is calculated from which Péclet numbers are derived. These results are compared with computer experiments with reasonable agreement. The second case is of almost inelastic interactions when the percolating particle slithers and drops into the next encounter in the fixed bed. The distributions of landing angles (the angles which the percolating particles make on the spherical obstacle on landing) and the Péclet numbers are deduced and differ substantially from random models. It is shown that there is low radial diffusion and the Péclet number is high.
Research on the controlling thermal defocus aberration for the infrared imaging system based on wavefront coding

We describe the application of wavefront coding technique for infrared imaging system to control thermal defocus. For traditional infrared imaging system, athermalization is necessary to maintain imaging performance which may increase complexity and cost of the imaging system. Wavefront coding includes a phase mask at the pupil which can re-modulate wave front so as to produce an encoded image. After digital processing, the system is insensitive to defocus. In this paper, the combination of wavefront coding technique and infrared imaging system has been discussed. We report here the optic design of the wavefront coding IR system based on Zemax. The phase mask is designed to ensure that the modulation transfer function (MTF) is approximately invariant in the range of working temperature. Meanwhile, we designed three IR systems to put up contrast experiments. System one and two are designed to compare the influence before and after the insertion of phase mask. System three is designed to compare the imaging performance before and after reducing lens in wavefront coding IR system. The simulation results show that the infrared imaging system based on wavefront coding can control thermal defocus in a temperature varying from -60ºC to 60 ºC, at the same time the weight and cost of optical elements are reduced by approximately 40%.
Design and Analysis of Ecological Experiments

Contributors 1: Samuel M. Scheiner: Theories, Hypotheses, and Statistics 2: Robert J. Steidl and Len Thomas: Power Analysis and Experimental Design 3: Aaron M. Ellison: Exploratory Data Analysis and Graphic Display 4: Catherine Potvin: ANOVA: Experimental Layout and Analysis 5: Deborah E. Goldberg and Samuel M. Scheiner: ANOVA and ANCOVA: Field Competition Experiments 6: Samuel M. Scheiner: MANOVA: Multiple Response Variables and Multispecies Interactions 7: Peter S. Petraitis et al: ANCOVA: Nonparametric and Randomization Approaches 8: Carl N. von Ende: Repeated-measures Analysis: Growth and Other Time-dependent Measures 9: Paul W. Rasmussen et al: Time Series Intervention Analysis: Unreplicated Large-scale Experiments 10: Steven A. Juliano: Nonlinear Curve Fitting: Predation and Functional Response Curves 11: Ted Floyd: Logit Modeling and Logisitic Regression: Aphids, ANts and Plants 12: Randall J. Mitchell: Path Analysis: Pollination 13: Gordon A. Fox: Failed-time Analysis: Studying TImesto Events and Rates at Which events Occur 14: Philip M. Dixon: The Bootstrap and the Jackknife: Describing the Precision of Ecological Indices 15: Jay M. Ver Hoef and Noel Cressie: Spatial Statistics: Analysis of Field Experiments 16: Marie-Josee Fortin and Jessica Gurvitch: Mantel Tests: Spacial Structure in Field Experiments 17: James S. Clark and Michael Lavine: Payesian Statistics: Estimating Plant Demographic Parameters 18: Jessica Gurevitch and Larry V. Hedges: Meta-analysis: Combining the Results of Independent Experiments References Index
No impact of rural development policies? No synergies with CCTs? The IFAD-supported Gavião Project in Brazil

Abstract: We estimate the impacts of an IFAD-supported rural development project (Pro-Gavião). Because public policies are frequently implemented simultaneously rather than in isolation, we also estimate the impacts of—and possible synergies with—the Brazilian conditional cash transfer (CCT) program Bolsa Família. Developed jointly by IFAD and the State Government of Bahia, Pro-Gavião was a rural development project in 13 contiguous municipalities between 1997 and 2005. Census tract level data were extracted for the analysis from the 1995-96 and 2006 Agricultural Censuses. The evaluation uses propensity score matching to construct a control group of untreated census tracts, and a difference-in-differences estimation to identify impacts. The outcomes analyzed include land productivity, agricultural income and child labor. Although Pro-Gavião involved significant investments in the region, the results suggest little if any program impact, or synergies between the two programs. The unexpected null findings are robust to alternative approaches to identifying the treated census tracts, matching techniques, and heterogeneity in several dimensions. We show that the lack of impacts is not driven by adverse rainfall in the treated communities, or the influence of other programs in the control communities. Alternative explanations for the null results are explored.
Probabilistic model for two dependent circular variables

Motivated by problems in molecular biology and molecular physics, we propose a five-parameter torus analogue of the bivariate normal distribution for modelling the distribution of two circular random variables. The conditional distributions of the proposed distribution are von Mises. The marginal distributions are symmetric around their means and are either unimodal or bimodal. The type of shape depends on the configuration of parameters, and we derive the conditions that ensure a specific shape. The utility of the proposed distribution is illustrated by the modelling of angular variables in a short linear peptide. Copyright Biometrika Trust 2002, Oxford University Press.
Change Detection Based on a Transductive Inference in SAR Images

As the change detection based on Synthetic Aperture Radar (SAR) images that are difficult and very limited to acquire labeled samples are of low detection rate and high error rate, Thus a progressive transductive SVM algorithm based on original feature space for unsupervised change detection of SAR images is proposed. The pseudo-training set of the difference image is obtained using K-means clustering method without any prior information; Starting from these initial seeds, the progressive transductive SVM performs change detection in the original multitemporal feature space by gradually considering unlabeled patterns in the definition of the decision boundary between changed and unchanged pixels according to a transductive inference algorithm. Using dynamic region labeling rule, the algorithm not only achieves its rules of progressive labeling and dynamic adjusting, but also raises its speed at the same time. Experimental results obtained on different multitemporal SAR images show that, transductive inference algorithm that extract the information of unlabeled patterns improve the SVM classifier accuracy. These results confirm the effectiveness of the proposed approach.
Brief Review on Piper aduncum L., its Bioactive Metabolites and its Potential to Develop Bioproducts

: This literature brief review compiled the main biological activities and active chemical constituents that have already been isolated from Piper aduncum (Piperaceae), whose common name is spiked paper. In Brazilian Portuguese, it has been called pimenta-longa, aperta-ruão, pimenta de macaco, matico, erva de jaboti, jaborandi do mato, pimenta - de-fruto-ganchoso and tapa buraco . Extracts, essential oils (EOs) and compounds isolated from this species have exhibited remarkable fungicidal and insecticidal activities, besides antibacterial, antileishmanial, antioxidant, cytotoxic/antitumor, larvicidal, antiplatelet, molluscoidal and antiviral ones. P. aduncum is an endemic species in Brazil which has drawn researchers’ attention because of high contents of EOs that are extracted from its leaves, inflorescences and twigs. This study aimed at analyzing data on P. aduncum , its EOs, extracts and isolated compounds found in 45 research papers. Its major chemical constituent is definitely dillapiole, an arylpropanoid. Findings were carefully compiled by this brief review which reinforces the chemical and biological potential of this botanic species.
Comparative Analysis between Salmonella enterica Isolated from Imported and Chinese Native Chicken Breeds

Salmonella enterica is considered a significant threat to the global poultry industry and public health. In recent decades, antimicrobial resistance in Salmonella enterica has attracted increasing concern throughout the world. However, limited information is available on Salmonella enterica among different breeds of breeder chickens. Thus, this study aimed to compare the prevalence, serotype distribution, emergence of extended-spectrum beta-lactamases (ESBLs), antimicrobial resistance, and genetic resistance mechanisms in Salmonella enterica among different breeds of breeder chickens. A total of 693 samples (dead embryos, cloacal swabs, water, feed, environmental swabs, and meconium of newly hatched chicks) were selected and cultured for Salmonella from four breeder chicken farms in Shandong province, China, representing one imported and three native breeds, and the isolates were further serotyped. Of the Salmonella isolates, susceptibility to 11 antimicrobials of 5 classes, ESBL screening, and the presence of 21 antimicrobial resistance genes were determined in the present study. Overall, 94 (13.6%) isolates were recovered, which were divided into 3 serotypes (Salmonella Pullorum (n = 36), Salmonella Thompson (n = 32), and Salmonella Enteritidis (n = 26)). The results showed that the prevalence of Salmonella enterica isolates from the imported breeds was higher compared with the three domestic breeds. Eight of the ninety-four isolates were ESBL-positive strains, which were recovered from a domestic breed chicken farm. These eight ESBL-producing isolates were serotyped to Pullorum. Surprisingly, Salmonella Enteritidis (S. enteritidis) and S. pullorum were simultaneously isolated from a single dead embryo observed among one native breed. Meanwhile, among the Salmonella isolates, 53.2% (50/94) were multidrug-resistant strains, and 44.7% (42/94) of the isolates presented resistance to at least five antibiotics. Nearly all of the isolates (97.9%, 92/94) were resistant to at least one antimicrobial; one isolate of S. Thompson was resistant to seven antimicrobial agents belonging to four different classes. The carriage rate of three resistance genes (tetA, tetB, and sul1) among isolates from the imported breeds (87%, 70%, and 65.2%) was higher than that in those from domestic breeds (35.2%, 36.6, and 14.1%). To our knowledge, this is the first report of ESBLs-producing Salmonella isolated from a Chinese native breed of breeder chickens. Our results also highlight that a high prevalence of multidrug-resistant Salmonella enterica contamination is widespread among different breeds of breeder chickens, which is a major risk of food-borne diseases and public health.
FREQUENCY CONSTANTS FOR TRANSVERSE VIBRATION OF ANNULAR DISKS

Frequency constants for the transverse vibration of thin, annular disks are presented. All nine combinations of the boundary conditions, free, simply supported, and clamped, are included for Poisson’s ratios of 0.0, 0.3, and 0.5. Many of these cases have been treated earlier in the literature but with occasional, significant error. Consequently, several tests of the validity of the present solutions are described.
The effect of charcoal production on carbon cycling in African biomes

Using biomass for charcoal production in sub‐Saharan Africa (SSA) may change carbon stock dynamics and lead to irreversible changes in the carbon balance, yet we have little understanding of whether these dynamics vary by biome in this region. Currently, charcoal production contributes up to 7% of yearly deforestation in tropical regions, with carbon emissions corresponding to 71.2 million tonnes of CO2 and 1.3 million tonnes of CH4. With a projected increased demand for charcoal in the coming decades, even low harvest rates may throw the carbon budget off‐balance due to legacy effects. Here, we parameterized the dynamic global vegetation model LPJ‐GUESS for six SSA biomes and examined the effect of charcoal production on net ecosystem exchange (NEE), carbon stock sizes and recovery time for tropical rain forest, montane forest, moist savanna, dry savanna, temperate grassland and semi‐desert. Under historical charcoal regimes, tropical rain forests and montane forests transitioned from net carbon sinks to net sources, that is, mean cumulative NEE from −3.56 ± 2.59 kg C/m2 to 2.46 ± 3.43 kg C/m2 and −2.73 ± 2.80 kg C/m2 to 1.87 ± 4.94 kg C/m2 respectively. Varying charcoal production intensities resulted in tropical rain forests showing at least two times higher carbon losses than the other biomes. Biome recovery time varied by carbon stock, with tropical and montane forests taking about 10 times longer than the fast recovery observed for semi‐desert and temperate grasslands. Our findings show that high biomass biomes are disproportionately affected by biomass harvesting for charcoal, and even low harvesting rates strongly affect vegetation and litter carbon and their contribution to the carbon budget. Therefore, the prolonged biome recoveries imply that current charcoal production practices in SSA are not sustainable, especially in tropical rain forests and montane forests, where we observe longer recovery for vegetation and litter carbon stocks.
Reliability Prediction of the Distribution Network Based on Wavelet Neural Network with Quantum Particle Swarm Optimization Algorithm

Abstract For distribution networks with fuzzy network structure or large scale, traditional reliability assessment is limited by data collection and lack of data samples. Compared with traditional methods, the distribution network reliability prediction method can use fewer data to calculate and obtain reliability results, and its operation is simpler and more practical. In this paper, a distribution network original parameters and reliability prediction method based on wavelet neural network (WNN) and quantum particle swarm optimization algorithm (QPSO) is proposed. Firstly, given the blindness of mother wavelet selection, this paper analyses the error and running time through example analysis and selects the most suitable mother wavelet for distribution network reliability prediction. According to the characteristics of premature convergence of QPSO, the evolutionary speed factor and aggregation factor are introduced to modify the scaling factor to control the convergence of the algorithm. The improved QPSO is used to optimize the initial values and thresholds of the WNN. It can reduce their influence on the prediction results. Finally, the analysis results of different examples show that the method has higher forecast accuracy, better generalization ability, and stability. This method also provides new scientific ideas for the reliability prediction of distribution networks.