Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficiently Answering k-hop Reachability Queries in Large Dynamic Graphs for Fraud Feature Extraction

Instant messaging client (IMC) is now an essential tool for mobile users. In the representative IMC We Chat, cybercriminals deceive frauds, causing financial loss to normal users. Through statistical analysis, we find that certain fraud interactions commonly occur among WeChat users who are not k-hop neighbors. Therefore, efficiently answering whether the distance between two vertices is not longer than k at a certain time point (i.e., k-hop reachability queries) over the dynamic social graph of WeChat becomes a crucial task for fraud feature extraction in the detection system: it can help human experts quickly identify suspicious user interactions and the query results can be further used as the input feature to the downstream machine learning based detection methods. In this paper, we illustrate Bidirectional k-hop Reachability Query Processing over a Dynamic Graph (BREAD) that is used in WeChat for extracting the k-hop reachability feature for fraud detection. BREAD adopts the idea of estimating Personalized PageRank value. It first conducts the backward search from the destination vertex to construct an intermediate vertex set. Then, it performs a certain amount of random walks from the start vertex to see whether they can hit the intermediate vertex set, and the results are returned to answer k-hop reachability queries. We further propose $\text{BREAD}++$ that leverages the massive parallel processing power of GPU to achieve a considerable performance gain. Experiments on several large-scale dynamic graph benchmarks and the social graph of WeChat have demonstrated that $\text{BREAD}/\text{BREAD}++$ is superior than existing index-free competitors: our methods provide not only fast but also accurate responses and they are of practical value to k-hop reachability feature extraction in the fraud detection system of WeChat. Our implementation is available at https://github.com/XMUDM/BREAD.
A Novel Variable Lie Hypergraph Technique for Cluster Based Routing in Opportunistic Networks

In recent years, breakneck advancements in technology and the proliferation of wireless handheld devices have drawn tremendous interest to study. An opportunistic network (OppNets) refers to a number of wireless nodes opportunistically communicating with each other which does not rely on any ﬁxed structure. Due to this, routing packets from source to destination in OppNets remain a challenging issue. This paper proposes a multi-objective optimization approach for cluster based routing in OppNets that maximizes average delivery ratio, minimizes both the hop count and average delivery delay. We propose a novel Variable Lie hypergraph theory for a unanimous way of clustering and routing protocol to obtain the optimal solution. A Variable hypergraph is constructed by combining the Lie commutator. Variable hyperedges are the clusters, and the variable hypergraph transversal is the required set of cluster heads. Nodes of the variable hyperedges are positioned appropriately in an upper triangular matrix which is an element of upper triangular matrix Lie algebra. Furthermore, we propose the upper triangular routing matrix algorithm that ﬁnds the path in identifying the neighbour node by its location inside the upper triangular matrix using Lie commutators. Simulation results using real mobility traces are presented, manifesting the eﬀectiveness of the proposed scheme with very less time.
LARGE EDDY SIMULATION OF REACTIVE FLOW ON THE FIRE SIDE OF A STEAM CRACKING FURNACE

There has been a tremendous increase in the production of ethylene the of and this trend is expected to continue in the foreseeable future as well. Steam cracking- the principal process used for the production of ethylene has gained increasing interest, both at a fundamental as well as at a systems level, with the ultimate objective of making ethylene production energy-efficient and lesser polluting ( ). Numerical studies published in the past used Reynolds Averaged Navier-Stokes (RANS) equations coupled with the Radiative Transfer Equation (RTE) to solve for the mean flow field. However, for gaining deeper insights about the combustion occurring inside the furnace, unsteady flow features need to be captured using accurate and proven numerical techniques such as Large Eddy Simulation (LES). The challenges associated with LES of steam cracking furnaces include the presence of large spatial and temporal scale separation and the concomitant high computational cost, modeling accurate and sufficiently detailed chemistry to predict combustion and incorporating radiative heat transfer effects. In this study, the LES of a steam cracking furnace is carried out for the first time, by addressing the first two of the above-mentioned challenges using novel numerical methods and chemistry reduction techniques. LES solvers based on explicit time integration schemes, such as AVBP excellent numerical resolution and accuracy, they are limited in the maximum allowable time step that can be used, due to numerical stability requirements. in the case of simulations of furnaces due to small time steps and large flow-through times. In
Investigating Inter- and Intra-speaker Voice Conversion using Audiobooks

Audiobook readers play with their voices to emphasize some text passages, highlight discourse changes or significant events, or in order to make listening easier and entertaining. A dialog is a central passage in audiobooks where the reader applies significant voice transformation, mainly prosodic modifications, to realize character properties and changes. However, these intra-speaker modifications are hard to reproduce with simple text-to-speech synthesis. The manner of vocalizing characters involved in a given story depends on the text style and differs from one speaker to another. In this work, this problem is investigated through the prism of voice conversion. We propose to explore modifying the narrator’s voice to fit the context of the story, such as the character who is speaking, using voice conversion. To this end, two complementary experiments are designed: the first one aims to assess the quality of our Phonetic PosteriorGrams (PPG)-based voice conversion system using parallel data. Subjective evaluations with naive raters are conducted to estimate the quality of the signal generated and the speaker similarity. The second experiment applies an intra-speaker voice conversion, considering narration passages and direct speech passages as two distinct speakers. Data are then nonparallel and the dissimilarity between character and narrator is subjectively measured.
Antecedents of Relationship Conflict in Cross-Functional Project Teams

Relationship conflict is a pervasive phenomenon in cross-functional project teams. Although previous studies have demonstrated the dysfunctional effect of relationship conflict, the direct drivers of relationship conflict in cross-functional project teams remain unclear. To address this gap, a literature review and an advisory group discussion were performed to identify the antecedents of the relationship conflict framework. Afterward, a structural equation model (SEM) was used to confirm the influence of such antecedents on relationship conflict. Intrapersonal diversity, uncertain project task, organizational culture diversity, and inappropriate behavior positively influence relationship conflict. These findings help researchers better understand the drivers of relationship conflict as well as open a gateway for practitioners to control and manage relationship conflict for a successful cross-functional project.
An investigation of the effects of massage therapy on pain caused by umbilical vein catheter insertion in premature neonates: a clinical trial

Background: Infants are more vulnerable to the negative effects of pain than adults and older children. Non-drug pain management includes non-invasive, safe, and low-cost strategies which can be easily conducted by nurses. Massage therapy, as a non-drug method, can be effective in pain relief in infants. Aim: To find out how effective the massage therapy is in reducing the pain caused by umbilical vein catheter insertion in preterm infants. Methods: This present clinical trial study has been conducted in the Neonate Intensive Care Unit (NICU) ward of the Qaem hospital in Mashhad. Sixty-four preterm infants were divided into two groups randomly; control group and experimental one. The experimental group infants were given massage before the umbilical vein catheter insertion. Data collection was performed using questionnaires, checklists, and Premature Infant Pain Profile (PIPP). Results: The findings showed that the mean and standard deviation of pain scores were significantly lower in the experimental group (2.66±2.82) compared to the control group (9.78±3.63) (p<0.0001). Moreover, the mean changes of heart rate during the umbilical vein catheter insertion in the experimental and control groups were 6.84±7.19 and 18.50±7.95, respectively (p ˂ 0.0001). Conclusion: Although various results may be obtained using different pain assessment tools, the result which is presented here show that massage therapy can be effective in management and pain relief. Moreover, applying massage can improve some cardiovascular parameters in infants as a valuable finding.
Do the Rich Save More? Evidence from Brazil

This paper investigates whether rich households have a relatively higher saving rate. We consider a recent comprehensive household data set available for Brazil (POF 2018) to estimate several proxies for household lifetime income, and assess the saving rates across income groups. Although there is some evidence of a positive association between lifetime income and household saving rates, the results are sensitive to the prediction of lifetime income and the measure of household saving, in particular at the highest deciles of the income distribution.
The choice and architectural requirements of battery storage technologies in residential buildings

This study has been undertaken to gain a better understanding regarding the choice and architectural implications of battery storage technologies in a future built environment benefiting from renewable energy systems and energy storage technologies. As no models or tools have been found dealing specifically with the size of energy storage systems, this work has partially addressed this shortcoming through the consideration of a framework, within which these issues are explored. The study assessed the requirements of nine battery technologies for different residential building scales at the distribution level in the UK using quantitative methods. Three scenarios for 2030 were considered; the business as usual scenario, a scenario assuming electrification of heating and energy efficiency measures and a scenario in which one electric vehicle is assumed for each house. After deriving the nominal capacity for each technology and identifying key aspects for building integration, several spatial and other requirements, including footprint, volume, mass and cost for the scales of interest were estimated in each scenario considering daily autonomy. The investigation led to a schematic characterisation of the battery technologies according to their suitability across these requirements and their applicability in different building scales. The study showed that the architectural implications of the battery technologies’ integration considering daily autonomy are of little importance to designers. Attention should be given when more than one day of autonomy is applied. The choice of the most suitable technology according to its applicability in different building scales and different daily autonomy periods should also be carefully assessed.
Deployment Strategies for Service Innovation

In large organizations, local use of innovations is not enough; extracting the full use of the innovation requires deployment across the organization. The purpose of this paper is to explore strategies for the deployment of service innovations and factors influencing success. We adopt an inductive theory-building approach with a longitudinal embedded case study of ten successful service innovations. We find two deployment strategies: required adoption, in which subsidiaries are required to adopt innovations, and voluntary adoption, in which adoption is not compulsory—innovations are showcased, but the adoption decision is left to the subsidiaries. We have investigated the factors influencing deployment, including the decentralized nature of service innovation, fit with the internal and external context, extrinsic and intrinsic motivations, and handovers. Based on analyses of case evidence, we put forward research propositions accordingly. This study provides managerial guidance for multidivisional organizations to extract full value from service innovations. Although some results may be particular to the Chinese context, research in other contexts can broaden the generalizability of the findings.
Detecting Cyber Attacks by Applying MachineLearning Techniques

Because of the growth in cloud services, the growing number of web applications customers, and modifications to network infrastructure that connects devices running several operating systems, cyber security is facing new challenges. For this reason, network security components, sensors and insurance conspiracies must also be developed to meet the needs and concerns of the customers in order to combat new threats. In this post, we focus on combating application layer cyber assaults, which are rankedas the most dangerous threats and the most important test for network and cyber security. Most of this essay focuses on machine learning as a method to cope with model normal use and to detect cyber threats. Chart-based division technique and dynamic programming were used in order to obtain examples in the form of Perl Compatible Regular Expressions (PCRE) ordinary expressions. Information is gathered through HTTP requests made by the client to a web worker, which is used in the model. Using the CSIC 2010 HTTP Dataset, we've been able to demonstrate the effectiveness of our approach.
Gastroprotective effects of Methanol leaf extract of Desmodium velutinum (Fabaceae) and honey on ethanol-induced gastric ulcer in albino rat: The concept of combination therapy

Phytochemicals are known for their therapeutic effects through diverse mechanisms such as therapeutic modulators, substrate ligands, receptor ligands, enzyme cofactors, enzymes precursors, toxins scavengers, microbial growth inhibitors, therapeutic agents, and therapeutic enhancers in the treatment of various diseases and ailments. Folklorically, the indigenous people of Nigeria have used Desmodium velutinum (Fabaceae) for treatment of disease conditions such as headache, fever, diarrhea toothaches, ulcers, anti-oxidants, and pains. This study investigated the toxicity, and anti-ulcer effects of a combination of methanol leaf extract of Desmodium velutinum and honey in rats. Antiulcer studies were carried out using absolute ethanol rat models of ulceration. The rats were distributed into ten groups of five rats each. Group 1 served as a negative control, group 2 served as a positive control, group 3 served as untreated control, the test groups: groups 4 to 6 received crude extract of Desmodium velutinum at doses of 100, 250, and 500 mg/kg respectively, groups 7 to 9 received a combination of 1 ml honey and crude leaf extract of Desmodium velutinum at doses of 100, 250 and 500 mg/kg while group 10 received 1 ml of honey only. The acute toxicity showed that the extract caused no death in the mice at 5000mg/kg and therefore the LD50 is above 5000mg/kg. The result also showed that 500 mg/kg of the crude extract and 1 ml honey had 42.9% and 71.76 % inhibition of ulceration respectively, while their combination had 100% inhibition of ulceration among the rats treated with the combinations. The combination of methanol leaves extract of Desmodium velutinum and honey exhibited gastrotherapeutic effect in rats and suggest its continued usage as an antiulcer agent for the treatment of ulcer.
Dynamic Copula Processes

This paper presents a flexible new family of copula-based multivariate models designed for handling large numbers of variables (1) as random vectors in the static case or (2) as vector stochastic processes in the dynamic case. The family includes models with upper and lower tail dependence. Variables need not be exchangeable. To illustrate the model’s potential; three radically different examples have been constructed: a straight additive model, an additive conditional gamma model and a switching model. Archimedean copulas turn out to be a special case of the general model. Another advantage of these models it that it is easy to construct dynamic versions of the static copulas. Lastly, as these models are defined in a conditional independence framework, they are easy to simulate.
A STUDY ON SOME BIOLOGICAL ACTIVITIES AND IDENFTIFICATION OF AN ISOLATED COMPOUND FROMTHE LEAVES OF Eupatorium odoratum L.

In this study, leaves of a Myanmar indigenous medicinal plant, Eupatorium odoratum L. (Taw-bizat) were chosen for the investigation of phytochemical constituents andsome of the biological activities such as antitumor, antimicrobial, antioxidant and acute toxic properties. The phytochemical constituents, nutritional values and elemental contents were analyzed on the leaves sample by using appropriate reported methods. The methanol extract (25 μ g/disc) of the leaves sample was found to possess the antitumor activity against the tumor producing bacteria: Agrobacterium tumefaciens isolated from gall tissues of leaves of Sandoricum koetjape Merr. (Thitto). The crude extracts such as pet-ether, ethanol, methanol and ethyl acetate extracts were observed to be more potent than watery extract in antimicrobial activity against Bacillus subtilis , Staphylococus aureus , Pesudomonas aeruginosa , Bacillus pumilus , Candida albicans and Escherichia coli . However, the watery showed the antioxidant activity (IC 50 = 13.07  g/mL) higher than ethanol extract (IC 50 = 56.14  g/mL), determined by DPPH radical scavenging assay method. Both of watery and ethanol extracts did not show acute toxic effect up to 5000 mg/kg body weight dose on albino mice. From the separation of silica gel column chromatographic method, a bioflavonoid compound, 2´-hydroxy-4,4´,5´,6´-tetramethoxy chalcone(143-144  C, 0.12 %) was isolated from the active pet-ether extract of E. odoratum leaves. It was identified by UV-Visible, FT IR, 1 HNMR, 13 C NMR, and EI-MS spectroscopic methods and also by comparing with the reported data. This isolated chalcone compound was observed to exhibit higher antioxidant activity (IC 50 = 9.69  g/mL) than the watery and ethanol extracts.
Investigating the feasibility of social marketing baggy condoms: a study comparing double springers with standard latex.

The objective was to assess the feasibility of social marketing Double Springers (DS) brand baggy condoms by investigating their acceptability to consumers. The Double Springers condom is a latex condom with a baggy end shaped like a spiral. The condom was designed to give greater pleasure to both men and women while providing the same protection from HIV and pregnancy as a standard condom. The study recruited 250 couples 21-39 years old to test three DS and three standard condoms (SC) made of latex. Half of the couples were randomly assigned to try the DS first and half tried the SC first. Couples received three condoms in unmarked packages were given up to 10 days to try them and returned to the study site to be interviewed individually about their opinions regarding various attributes of the condom. They then received three of the other type of condom. After trying the second type the couples were interviewed about their experiences with that condom and were also asked to compare the two condom types. The results were analyzed using statistical tests for significant differences between groups and discriminant analysis. Only three couples dropped out of the study after trying the first condom and no couples reported adverse effects. Respondents overwhelmingly preferred the standard latex condoms. This finding held for all factors that were probed whether ratings were of the DS condom alone or in comparison to the SC. With regard to specific advantages purportedly associated with baggy condoms of those interviewed 5 percent said that the DS stimulated pleasurable sensations 59 percent thought the DS was too large and around 30 percent thought the DS was too thick and/or had too much lubrication. Respondents preferred the SC over the DS for sensitivity (80 percent) stimulation (79 percent) and appearance (75 percent). Only 16 percent said they were more likely to buy the DS than the SC with another 4 percent saying the chances of them buying the two condoms were equal. The DS scored its highest ratings for the following factors: 25 percent of respondents preferred DS condoms lubrication 22 percent preferred their strength and 20 percent said they were easier to put on. Discriminant analysis failed to identify any factors that would distinguish a niche market for the DS. Baggy condoms such as the Inspiral and Double Springers are marketed as innovations in condom design that increase pleasure for both men and women. Expectations of a product can influence perceptions and marketing can effectively appeal to consumers who are receptive to product innovations. This study found that in a blind test where consumers do not have such expectations they seem surprised by the size and appearance of the DS. A marketing campaign that prepares consumers for these differences and stresses the potential for greater pleasure with protection could influence consumers perceptions. But the strongly negative results of this study make designing a cost-effective social marketing campaign for Double Springers a risk. (authors)
Text Classification and Prediction in the Legal Domain

We present a case study on the application of text classification and legal judgment prediction for flight compensation. We combine transformer-based classification models to classify responses from airlines and incorporate text data with other data types to predict a legal claim being successful. Our experimental evaluations show that our models achieve consistent and significant improvements over baselines and even outperformed human prediction when predicting a claim being successful. These models were integrated into an existing claim management system, providing substantial productivity gains for handling the case lifecycle, currently supporting several thousands of monthly processes.
Low-resource Neural Machine Translation: Benchmarking State-of-the-art Transformer for Wolof<->French

In this paper, we propose two neural machine translation (NMT) systems (French-to-Wolof and Wolof-to-French) based on sequence-to-sequence with attention and Transformer architectures. We trained our models on the parallel French-Wolof corpus (Nguer et al., 2020) of about 83k sentence pairs. Because of the low-resource setting, we experimented with advanced methods for handling data sparsity, including subword segmentation, backtranslation and the copied corpus method. We evaluate the models using BLEU score and find that the transformer outperforms the classic sequence-to-sequence model in all settings, in addition to being less sensitive to noise. In general, the best scores are achieved when training the models on subword-level based units. For such models, using backtranslation proves to be slightly beneficial in low-resource Wolof to high-resource French language translation for the transformer-based models. A slight improvement can also be observed when injecting copied monolingual text in the target language. Moreover, combining the copied method data with backtranslation leads to a slight improvement of the translation quality.