Miracle-dz/UniFAR-FTUs huggingface dataset:
An Overview on Edge Computing Research

With the rapid development of the Internet of Everything (IoE), the number of smart devices connected to the Internet is increasing, resulting in large-scale data, which has caused problems such as bandwidth load, slow response speed, poor security, and poor privacy in traditional cloud computing models. Traditional cloud computing is no longer sufficient to support the diverse needs of today’s intelligent society for data processing, so edge computing technologies have emerged. It is a new computing paradigm for performing calculations at the edge of the network. Unlike cloud computing, it emphasizes closer to the user and closer to the source of the data. At the edge of the network, it is lightweight for local, small-scale data storage and processing. This article mainly reviews the related research and results of edge computing. First, it summarizes the concept of edge computing and compares it with cloud computing. Then summarize the architecture of edge computing, keyword technology, security and privacy protection, and finally summarize the applications of edge computing.
Optimal Seeds Discovery of Traffic Congestions

With the rapid adoption of wireless sensor networks (WSNs) into smart cities and vehicle networks, traffic problems can be evaluated and predicted in real-time. In this paper, we propose a data-driven approach to find out the most influential causes of traffic congestions. We first find the top most influential regions and use the Fortune’s algorithm to partition the city. Second, we propose a model with three correlations to measure the dependency between two traffic events, which are spatial correlation, temporal correlation, and logical correlation. Third, we adapt the Independent Cascade model with a pruning algorithm to address traffic congestions. At last, we conduct intensive experiments on large real-world GPS trajectories generated by more than 10,200 taxis in Shanghai to demonstrate the performance of our approaches.
On the Vertex-Connectivity of an Uncertain Random Graph

In many practical problems, randomness and uncertainty simultaneously appear in one complex system or network. When graph theory is applied to these problems, these complex systems or networks are usually represented by uncertain random graphs, in which some edges exist with degrees in probability measure, and some other edges exist with degrees in uncertain measure. In this paper, we focus on the connectivity of uncertain random graphs with respect to vertices. We propose the concepts of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-vertex-connectivity index and the connectivity of an uncertain random graph. The former is the chance measure that an uncertain random graph is <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-vertex-connected, and the latter is an uncertain random variable, which characterizes the connectivity of the uncertain random graph with respect to vertices. We discuss some properties of these concepts. Methods and formulas are also presented for calculating the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-vertex-connectivity index, and the distribution and expected value of the connectivity of an uncertain random graph.
A Lane Tracking Method Based on Progressive Probabilistic Hough Transform

Lane departure warning systems have gained considerable research interest in the past decade for its promising usage in automotive, where lane detection and tracking is applied. However, it is a challenging task to improve the robustness of lane detection due to environmental factors, such as perspective effect, possible low visibility of lanes, and partial occlusions. To deal with these issues, we propose a reliable vision-based real-time lane markings detection and tracking system that can adapt to various environmental conditions. The lane detection is composed of three stages: pre-processing, Adaptive Region of Interest (AROI) setting, and lane marking detection and tracking. In the pre-processing stage, smoothing and edge detection operators are applied on input frames to automatically obtain binary images, then, lane markings segmentation are carried out. After that, An Adaptive Region of Interest is extracted to reduce the computational complexity. In the subsequent detection stages, Kalman filter is employed to track road boundaries detected in the AROI using Progressive Probabilistic Hough Transform (PPHT) in the next frame. Based on road boundaries and the vehicle’s position, the proposed algorithm decides if the vehicle has drifted off the lane. For the performance evaluation of lane detection and tracking, real-life datasets for both urban roads and highways in various lighting conditions are used. Applying our method to Catltech dataset, the average correct detection rate is 93.82%. In addition, the proposed method outperforms that of the state-of-the-art methods in processing time (21.54ms/frame).
Pulse of the City: Spatio-Temporal Twitter Content Analysis

The continuous, online processing of streaming data generated by smart city settings offers opportunities for richer, data-driven understanding of modern urban life. In this paper, we focus on the application of machine learning for highly localized classification of a broad set of urban activities from streaming twitter social media data. We build a platform for continuous ingestion of twitter data, spatio-temporal clustering of the tweets, and online topic and sub-topic extraction through hierarchical classification. We demonstrate results within Manhattan, and show that we can identify urban activities at the spatio-temporal resolution of 3 hours within a single city block. We also demonstrate how our streaming platform can be extended to support multi-modal sensing across dense urban environments, and scale to cover vast geographical areas.
An Efficient v-Minimum Absolute Deviation Distribution Regression Machine

Support Vector Regression (SVR) and its variants are widely used regression algorithms, and they have demonstrated high generalization ability. This research proposes a new SVR-based regressor <inline-formula> <tex-math notation="LaTeX">$:v$ </tex-math></inline-formula>-minimum absolute deviation distribution regression (<inline-formula> <tex-math notation="LaTeX">$v$ </tex-math></inline-formula>-MADR) machine. Instead of merely minimizing structural risk, as with <inline-formula> <tex-math notation="LaTeX">$v$ </tex-math></inline-formula>-SVR, <inline-formula> <tex-math notation="LaTeX">$v$ </tex-math></inline-formula>-MADR aims to achieve better generalization performance by minimizing both the absolute regression deviation mean and the absolute regression deviation variance, which takes into account the positive and negative values of the regression deviation of sample points. For optimization, we propose a dual coordinate descent (DCD) algorithm for small sample problems, and we also propose an averaged stochastic gradient descent (ASGD) algorithm for large-scale problems. Furthermore, we study the statistical property of <inline-formula> <tex-math notation="LaTeX">$v$ </tex-math></inline-formula>-MADR that leads to a bound on the expectation of error. The experimental results on both artificial and real datasets indicate that our <inline-formula> <tex-math notation="LaTeX">$v$ </tex-math></inline-formula>-MADR has significant improvement in generalization performance with less training time compared to the widely used <inline-formula> <tex-math notation="LaTeX">$v$ </tex-math></inline-formula>-SVR, LS-SVR, <inline-formula> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula>-TSVR, and linear <inline-formula> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula>-SVR. Finally, we open source the code of <inline-formula> <tex-math notation="LaTeX">$v$ </tex-math></inline-formula>-MADR at <uri>https://github.com/AsunaYY/v-MADR</uri> for wider dissemination.
Proactive user engagement via friendly survey and data-driven methodologies

In this paper, we present CAROL (unConventionAl suRvey methOdoLogy) to collect users’ opinions, to analyze them effectively, and to graphically provide interesting summaries in near-real-time. CAROL has been designed to collect citizens’ opinions, needs, and a perception that can be very useful to redesign cities and drive the innovation process. To this aim, particular importance is given to the architecture implemented to collect the data, which involves sending voice messages instead of text, allowing users greater freedom of expression. Moreover, to make the survey more friendly, an initial analysis is done in real-time thanks to an intuitive dashboard, which shows the first results in the form of graphs and charts, updated after each message. Finally, a more in-depth analysis can be carried out at the end of the survey, thanks to text-mining techniques adapted to the context. As use case, the proposed methodology has been tested in a public event organized by Politecnico di Torino and addressed to female students, with the aim to collect their ideas about new services/opportunities that can be offered to support women in STEM.
Archaeal communities in two disparate deteriorated ancient wall paintings: detection, identification and temporal monitoring by denaturing gradient gel electrophoresis

In the present study we describe the detection of Archaea in two different deteriorated ancient wall paintings, located in Austria and Spain, under different humidity/salinity regimes and climates. Archaeal communities were analyzed by combination of denaturing gradient gel electrophoresis (DGGE) of PCR-amplified DNA encoding 16S rRNA and the construction of clone libraries. DGGE analysis was used for temporal monitoring of the archaeal communities as well as for screening of the clone libraries. Selected clones were compared with band patterns obtained from the original samples and sequenced. Sequence analyses documented the existence of species belonging to well-characterized halophilic and alkaliphilic Archaea.
EFFECT OF GROWING YEAR AND APPLICATION OF A MULTI-YEAR CALIBRATION FOR PREDICTING QUALITY PARAMETERS BY NEAR INFRARED REFLECTANCE SPECTROSCOPY IN WHOLE-PLANT CORN FORAGE

Near infrared reflectance spectroscopy analysis (NIRA) to predict quality parameters in whole-plant corn forage was investigated. Quality parameters studied included acid detergent fiber (ADF), in vitro dry matter digestibility (IVDMD) and crude protein (CP). Samples of whole-plant corn forage were collected during three growing years (1984, 1985, 1986) across six geographical locations in Ontario, Canada and were harvested at an average 35% dry matter content. Samples were randomly divided into two sets: a calibration (CAL) set to develop NIRA equations and a testing (TEST) set to validate these equations. NIRA calibrations for ADF, IVDMD and CP percent were performed for each growing season across locations. A multi-year calibration was also developed with samples drawn from the three growing years. The accuracy of the NIRA predictions was assessed by the standard error of the estimate (SEE), bias or the mean difference between laboratory and NIRA data, the coefficient of determination (r2) and the slop.
Specificity of Lepidelphax pistiae (Hemiptera: Delphacidae) to Pistia stratiotes (Araceae)

The delphacid Lepidelphax pistiae was found on water lettuce in Argentina. Nymphs and adults did not survive past seven days on 29 species of test plants, and no progeny were produced. In contrast, survival and reproduction were high on water lettuce. Results suggest that L. pistiae is monospecific to water lettuce.
Nest defence of nesting chinstrap penguins (Pygoscelis antarctica) against intruders

We tested some predictions of parental investment theory by studying the aggressive behaviour of colonial nesting chinstrap penguins (Pygoscelis antarctica) against human intruders into their nesting territories. We tested for differences in the aggressive behaviour of penguins according to offspring age (eggs vs. chicks), offspring number, nest location in the colonies (central vs. peripheral) and sex. Offspring age was the main factor influencing nest defence, although nest location and sex were also important. Chicks were defended more strongly than eggs, in accordance with changes in the reproductive value of offspring, and this increase in aggressiveness was not related to revisitation of the same individuals. The level of aggression of penguins breeding in central sites was higher than that of peripheral birds, a difference that could be due to the lower residual reproductive value of central-nesting, probably older, birds. The stronger aggressiveness of males could be due to a combination of factors related to sexual selection and life-history traits. Offspring number did not affect the level of nest defence.
Deposition of modern pollen and plant macroremains in a hypersaline prairie lake basin

Comparisons between current vegetation patterns and deposition of modern pollen and plant macroremains in a saline lake basin on the northern Great Plains are used to assess the value of plant remains as indicators of past local vegetation dynamics and lake-level changes. Results indicate that both modern pollen spectra and assemblages of plant macroremains reflect clearly the composition of the local vegetation, whereas plant macroremains best reflect lake size. Cactaceae pollen and seeds are confined to upland prairie deposits. Liguliflorae (Compositae) and Leguminosae pollen, Selaginella densa microspores, and Euphorbia and Cruciferae seeds are more abundant in prairie upland deposits than in shoreline or lacustrine environments. An abundance (> 50%) of Ruppia pollen distinguishes near-shore lake sediments, indicating that this taxon is a useful marker of shallow shoreline environments in saline lakes. Seeds of Chenopodiaceae, Erigeron, Cruciferae, and Cyperaceae, as well as Chara oogonia, are more abu.
Autotrophic growth of anaerobic ammonium-oxidizing micro-organisms in a fluidized bed reactor

An autotrophic, synthetic medium for the enrichment of anaerobic ammonium-oxidizing (Anammox) micro-organisms was developed. This medium contained ammonium and nitrite, as the only electron donor and electron acceptor, respectively, while carbonate was the only carbon source provided. Preliminary studies showed that the presence of nitrite and the absence of organic electron donors were essential for Anammox activity. The conversion rate of the enrichment culture in a fluidized bed reactor was 3 kg NH4 + m-3 d-1 when fed with 30 mM NH4 +. This is equivalent to a specific anaerobic ammonium oxidation rate of 1000-1100 nmol NH4 +h-1 (mg volatile solids)-1. The maximum specific oxidation rate obtained was 1500 nmol NH4 +h-1 (mg volatile solids)-1. Per mol NH4 + oxidized, 0.041mol CO2 were incorporated, resulting in a estimated growth rate of 0.001 h-1. The main product of the Anammox reaction is N2, but about 10% of the N-feed is converted to NO3 -. The overall nitrogen balance gave a ratio of NH4 --conversion to NO2 --conversion and NO3 --production of 1:1-31++0.06:0.22+0.02. During the conversion of NH4 + with NO2 -, no other intermediates or end-products such as hydroxylamine, NO and N2O could be detected. Acetylene, phosphate and oxygen were shown to be strong inhibitors of the Anammox activity. The dominant type of micro-organism in the enrichment culture was an irregularly shaped cell with an unusual morphology. During the enrichment for Anammox micro-organisms on synthetic medium, an increase in ether lipids was observed. The colour of the biomass changed from brownish to red, which was accompanied by an increase in the cytochrome content. Cytochrome spectra showed a peak at 470 nm gradually increasing in intensity during enrichment.
Effects of an amino-oligosaccharide on diet degradation and milk production in dairy cows

The objective of this study was to evaluate the influence of an amino-oligosaccharide (AAOS) on milk production and in vitro dry matter degradation (IVDMD) of a total mixed ratio (50:50 forage:concentrate) for lactating dairy cows. Treatments (diets) were control (0 g AAOS) and AAOS (0.17% of diet, DM basis). In vitro incubations were carried out at 12, 24, 48 and 70 h. Sixty multiparous Jersey cows (81±7 days in milk) were randomly assigned to the two treatments. Milk production and milk components were evaluated during 42 days. The IVDMD was reduced by AAOS only at 12 h incubation. Cows fed AAOS showed similar dry matter intake, milk yield, milk fat, milk non-fat solids and milk lactose as compared to control. However, AAOS increased milk protein percentage and decreased milk urea-nitrogen, as compared to control.
Impact of gender-based violence on psychological distress and happiness in León (Nicaragua)

Abstract The researchers’ aim for the current study is to analyze the impact of gender-based violence on mental health and happiness. The sample is composed of 136 women victims of intimate partner violence, who were living in poverty. The participants contacted through the country’s Commissariat for Women and Children and other associations working with the National Police from Nicaragua, a country with low levels of development. The results of our structural equation model show that the frequency of abuse has a direct effect on psychological distress and an indirect effect on overall happiness. The deterioration of mental health and social support have a direct effect on overall happiness. Consequently, emotional recovery and social support play an important role in the future of women victims of gender-based violence. This information can be useful to reduce psychological distress and improve care for women in specialized services.
Preservation of Gray Matter Volume in Early Stage of Bipolar Disorder: A Case for Early Intervention: Préservation du volume de matière grise au stade précoce du trouble bipolaire: un cas pour intervention précoce

Objective: It has been proposed that different stages of the bipolar disorder might have distinct neurobiological changes. However, the evidence for this has not been consistent, as the studies in early stages of the illness are limited by small sample sizes. The purpose of this study was to investigate the gray matter volume changes in bipolar patients who recently recovered from their first episode of mania (FEM). Methods: Using a whole-brain voxel-based analysis, we compared the regional gray matter volumes of 61 bipolar patients who have recovered from their FEM in the past 3 months with 43 age- and gender-matched healthy participants. We also performed a series of subgroup analyses to determine the effects of hospitalization during the FEM, history of depressive episodes, and exposure to lithium. Results: No statistically significant difference was found between gray matter volumes of FEM patients and healthy participants, even at a more liberal threshold (P < 0.001, uncorrected for multiple comparisons). Voxel-based subgroup analyses did not reveal significant gray matter differences except for a trend toward decreased gray matter volume in left lateral occipital cortex (P < 0.001, uncorrected) in patients with a previous history of depression. Conclusion: This study represents the largest structural neuroimaging investigation of FEM published to date. Early stage of bipolar disorder was not found to be associated with significant gray matter volume changes. Our findings suggest that there might be a window of opportunity for early intervention strategies to prevent or delay neuroprogression in bipolar disorder.
Floral and vegetative morphometrics of three Platonia insignis Mart. (Clusiaceae) populations, a native tree from the Brazilian Amazon

Platonia insignis Mart. (Clusiaceae), the bacurizeiro, is a native tree species from the Brazilian Amazon forests. Three populations of P. insignis have been observed in the north-east region of the state of Maranhão that differ in flower color: the red population that produces dark pink flowers, the pink population that produces light pink flowers, and the white population with yellowish-white flowers. From multivariate statistical analysis, we aimed at characterizing such populations using morpho-anatomical leaf and flower morphology parameters. A total of 40 P. insignis individuals have been sampled in the cities of São Luís and Chapadinha. The morphological traits varied more than the anatomical traits. Area, fresh mass, and dry mass were the leaf parameters that show more variations. Platonia insignis have hypostomatic or amphihypostomatic leaves. The length of the gynoecium+the length of the nectary, the total length and the length of gynoecium were the principal components considering flower analysis. The three populations did not show significant differences nor did they group using Ward's method. Individuals from the Chapadinha and São Luís red population have been separated according to leaf and flower morphological traits, and the morphological difference between individuals may represent early stages of geographical speciation.
Breakdown of plant carbohydrates in the digestive tract of pigs fed on wheat‐ or oat‐based rolls

Cell wall materials from various cellular tissues of cereals may potentially influence the digestion and absorption processes in different ways. The objective of the present investigation was to study the breakdown of plant carbohydrates in the gastrointestinal tract of pigs fed a low-fibre (LF; 65 g kg−1 dry matter) wheat flour-based diet and two high-fibre diets with added insoluble fibre from wheat bran (HFWB; 112 g kg−1 dry matter) or soluble fibre from oat bran (HFOB; 108 g kg−1 dry matter). The diets were formulated to provide ∼0.31 energy from fat, ∼0.18 energy from protein and ∼0.51 energy from carbohydrates and were offered as baked rolls to eight ileum-cannulated hypercholesterolemic pigs in a crossover design. Carbohydrates were the predominant ileal constituent, with most of the carbohydrates present as non-starch polysaccharides (NSP). Starch in all diets was almost completely digested at this site of the gastrointestinal tract, with digestibility values above 0.99. The ingested amount of NSP was quantitatively recovered in ileal materials with the wheat-based diets, while there was a significant loss of 0.27 of NSP primarily as mixed linked (13)(14)--D-glucan with diet HFOB. The concentration and flow of lactic acid were also highest in the ileum after feeding diet HFOB, indicating that -glucan stimulated lactic acid formation. Any soluble components that reached the large intestine were almost completely broken down, while the digestibility of insoluble NSP constituents was significantly lower for diets LF and HFWB than for diet HFOB. The high degradation of oat bran resulted in a lower effect on faecal dry and wet bulking than was found with wheat bran. In conclusion, cereal starch was practically completely degraded in the small intestine, while the site and extent of NSP degradation, lactic acid formation and bulking properties were influenced by the fibre source. © 2000 Society of Chemical Industry