Miracle-dz/UniFAR-FTUs huggingface dataset:
Cannabis use among a sample of adult male Jordanian inmates: use, consequences and associated factors

ABSTRACT Cannabis is considered the most commonly used illicit substance worldwide. Reports indicate an increase in its spread and use in developing countries such as Jordan. However, no studies report cannabis use in Jordan and its effects on the health of users. Therefore, the current study aims to assess the prevalence of cannabis ever use and the problematic consequences of cannabis use. Methods A cross-sectional descriptive study was conducted among 1,000 participants who were inmates in correctional facilities in Jordan. Data were collected using a self-report tool that included questions about participants’ demographics, cannabis use history, and the Cannabis Abuse Screening Test (CAST). Results A 36% prevalence of cannabis ever use was reported, with 17.9% showing problematic consequences of cannabis use. Being a smoker and having a history of alcohol and other drugs ever use was significantly associated with demonstrated problematic consequences of cannabis use. Conclusion The current study reports the prevalence of cannabis ever use among a sample of Jordanian adults, problematic consequences, and smoking, alcohol, and other drug use as factors associated with cannabis use. Our findings indicate the need for health prevention programs to target youth and adults to emphasize the harmful effects of cannabis use.
Approximation and Analysis of Single Band FIR Pass Integrator Centered around Mid-band Frequencies with Degree k = 1, 2, 3

In this paper, a modified Finite Impulse Response based linear Pass integrator for centered frequency, ranging between 0.1 π to 0.9 π has been realized. Both the cases have been considered i.e. for what values the phase response is of use and where the phase response has zero value. An iterative formula has been used to calculate the weights depending upon the Transfer Functions, and applying differentiation method. A flat output approximation for the desired frequency ω has been applied for which the results overlap with the ideal integrator. Performance comparison of the proposed integrator has been done with the previous one and relative percentage errors have been observed for both cases implemented. Graphical analysis has also been carried out for frequency responses having degree greater than one (i.e. k = 2, 3, 4) for both cases of proposed integrator and compared with the ideal integrator's response.
Data Mining with Associated Methods to Predict Consumer Purchasing Patterns

: Technology is developed and utilized as an honest computer in order that it can provide useful information. With the aim of developing and meeting business objectives, the utilization of sales transaction data in minimarket GP is processed into information or knowledge as a recommendation to ascertain the possible value of purchased simultaneously. This processing uses data mining. Database buildup in computerized systems is justified by getting added value from this data set. Data mining can predicts trends and therefore the nature of business behavior which is extremely useful to support important deciding. The algorithm wont to form the association rules during this study is CT-Pro. CT-Pro algorithm may be a development of FP-Growth. The difference is within the second step where FP-Growth creates the FP-Tree arrangement while CT-Pro makes the Compressed FP-Tree (CFP-Tree) arrangement. The CT-Pro algorithm process by analyzing employing a tree system where the things most frequently purchased become root and other items will follow the basis. The CFP-Tree process will provide levels for every transaction and facilitate mining results. CT-Pro algorithm implementation with CFP-Tree arrangement applied to data mining systems is in a position to research sales data for 3 months, namely January 2020 – March 2020 with a complete data record of 1.303 and 320 sales transactions at minimarket GP become information or knowledge. The results of this study are the relationship between the tendency of products that are bought together based on categories in a kind of percentage to be used as a recommendation in structuring the position of items that are mutually frequent in certain categories
Model to classify and reduce rework in the production of digital routers in a PIM Company

Rework has been a challenge for organizations, especially in Brazil, where there is still a lot of waste of resources (IDB, 2018; EMBRAPA, 2018). This case study aims to contribute to improving the classification and reduction of rework in the sectors involved with the production of digital routers from the company EX da Amazônia (fictitius name), located in the Industrial Pole of Manaus. To this end, bibliographic research and methodology with seven phases, allowed to develop and apply a questionnaire to 71 employees who work in seven sectors involved with the processes of the organization's digital routers. The analysis was carried out with descriptive statistics, which allowed the identification of the best concepts for the term, the main problems, their causes, and effects, as well as reaching the main conclusion that the best model to classify and reduce reworks in the organization, must be developed by senior management, based on an interdepartmental approach, with diagnoses of the situation in each department, as well as the adoption of an annual plan to combat rework, supported by the use of information and communication technologies, awareness campaigns, continuous training, IT tools, quality approaches for improvement projects, audits, standardization, identification and dissemination of good practices, and recognition of employees.
Relationship between nomophobia and occupational performance among university students

Introduction Nomophobia is a contemporary phobia that emerged in the digital age and is becoming increasingly common. University students are at higher risk for nomophobia. This study aims to develop an understanding of nomophobic university students’ problem areas in their daily occupations. Methods This cross-sectional study was conducted with 181 university students between January and March 2020. The Nomophobia Questionnaire was used to determine the students’ level of nomophobia and they were separated into groups based on nomophobia severity. The Canadian Occupational Performance Measure was used to determine the students’ occupational performance and satisfaction in the occupations they identified as being most problematic for them. Canadian Occupational Performance Measure scores were compared between nomophobia severity groups. Results All students in the study had some degree of nomophobia (mild = 56, moderate = 95, severe = 30). Canadian Occupational Performance Measure performance and satisfaction scores were significantly lower in students with severe nomophobia compared to the mild/moderately nomophobic students (p<.05). The occupations of greatest concern were in the areas of productivity (studying, 20.89%), self-care (sleeping, 9.87%), and leisure (doing sport, 8.23%). Conclusion This study demonstrated a relationship between nomophobia and occupational performance difficulties in university students. Occupational therapists should consider nomophobia when evaluating occupational performance difficulties in university students.
Rail Fastener Positioning Based on Double Template Matching

For global template matching (GTM), which is commonly used in the positioning of rail fasteners, only the fastener template is used to search the global image in both two dimensions, which will result in errors in two dimensions, and the lower positioning accuracy will be caused. A positioning method for rail fasteners based on double template matching (DTM) is proposed in this paper, in which the double template contains the rail template and the fastener template. First, the rail template is used to scan the original image in horizontal dimension, and the squared Euclidean distance (SED) is used to obtain the rail positioning in the original image. Combining with the prior knowledge of the fastener template image, the image composed of the rail and the fastener can be obtained, which is called the Rail Area Map (RAM) in this paper. Then, after preprocessing the RAM and the fastener template image, the fastener template image is used to scan the RAM in vertical dimension, and the normalized correlation coefficient (NCC) is used to calculate the similarity between the template and the subgraph of the RAM to achieve precise positioning of the fastener. The proposed DTM method adopts a positioning strategy from coarse to fine, and two templates are used to complete different positioning tasks in their own dimension, respectively. Due to the rail can be precise positioned in horizontal dimension, the error of the fastener positioning in the horizontal dimension can be avoided, and thus, the positioning accuracy can be improved. Experiments on the on-site line fastener images prove that the proposed method can effectively achieve the precise positioning of fasteners.
Cooperative Loitering Munition Swarm Online Patrolling Route Planning with Nonlinear Seeker Measurement

With the development of autonomous systems, the operational use of loitering munition is shifting from the following of a preplanned fixed route without communication to smart decision-making and collaborative cooperation with sharing information. In this paper, we study the autonomous decision-making and cooperative control strategy of online patrolling for a swarm of loitering munitions using communication to coordinate their route based on maximizing the information they gathered in the operation region. Taking the non-Gaussian nonlinear property of airborne radar seeker into account, we utilized a particle filter-based method to evaluate or to predict the information quality of each action candidate. We also implemented a coordinate descent scheme to enable a distributed and scalable swarm decision-making. Simulation results show that the proposed method provides a better estimation than baselines without the need for external or centralized decision agent.
Subsurface flow and associated oxygen transfer induced by turbulence in a gravel bed river

A model for the subsurface flow and associated oxygen transfer induced by surface flow and slip velocity is presented in a gravel bed river. The shear velocity (U *) and hydraulic conductivity (K) were used to characterize the surface flow and subsurface flow, respectively. The subsurface flow field was described by using the Darcy and the Brinkman equations. The interaction between surface and subsurface flow can be represented by the slip velocity via the shear velocity (U *) and hydraulic conductivity (K). The effect of turbulence above the permeable surface on the subsurface flow can also be described by the Reynolds stress in terms of eddy viscosity (νt ). The model was found to substantially reproduce the experimental time-averaged subsurface velocity profiles. It was shown that turbulence penetrating through permeable sediments is limited to a thinner layer within a few centimetres from the sediment/water interface. This result can be useful to evaluate the effect of turbulence over the permeable surface on oxygen penetration into the sediment.
Neural network models for phonology and phonetics

This paper argues that if phonological and phonetic phenomena found in language data and in experimental data all have to be accounted for within a single framework, then that framework will have to be based on neural networks. We introduce an artificial neural network model that can handle stochastic processing in production and comprehension. With the “inoutstar” learning algorithm, the model is able to handle two seemingly disparate phenomena at the same time: gradual category creation and auditory dispersion. As a result, two aspects of the transmission of language from one generation to the next are integrated in a single model. The model therefore addresses the hitherto unsolved problem of how symbolic-looking discrete language behaviour can emerge in the child from gradient input data from her language environment. We conclude that neural network models, besides being more biologically plausible than other frameworks, hold a promise for fruitful theorizing in an area of linguistics that traditionally assumes both continuous and discrete levels of representation.
A novel approach for scene classification from remote sensing images using deep learning methods

ABSTRACT Deep learning plays a major task in classification of unsupervised data, which utilises network enhanced learning. This technique proves to be powerful in remote sensing (RS) field for spatial data classification. In the existing environment, huge amounts of data from the earth observation satellites known as satellite images time series (SITS) are gathered, which can be utilised for observing the areas related to geography over through time. In this proposed model the time series model utilised is based on geography. There exists a challenge on how these types of information can be analysed in the field of remote sensing. Notable, techniques related to deep learning substantiated in dealing with remote sensing usually for classification of scene . In this paper, we propose an enhanced classification method involving Recurrent Neural Network (RNN) along with Random forest (RF) for land classification using satellite images, which are publicly available for various research purposes. We utilised spatial data gathered from the satellite images (i.e. time series). Our experimental classification is based on pixel and object-based classification. The attained analysis illustrates that the proposed model outperforms the other present day remote sensing classification techniques by producing 87% target accuracy of classification scene from satellite images.
Linking Organic Metabolites as Produced by Purpureocillium Lilacinum 6029 Cultured on Karanja Deoiled Cake Medium for the Sustainable Management of Root-Knot Nematodes

Root-knot nematodes pose a serious threat to agriculture and forest systems, causing significant losses of the crop worldwide. A wide range of chemical nematicides has traditionally been used to manage phyto-nematodes. However, due to their ill effects on the environment, biological control agents (BCAs) like Purpureocillium lilacinum that exhibit antagonistic effects on root-knot nematodes are preferred. The current study focused on identifying nematicidal metabolites produced by the fungus Purpureocillium lilacinum cultivated on akaranja deoiled cake-based liquid medium through bioactivity-guided fractionation against Meloidogyne incognita. Column chromatography of the ethyl acetate extract of fungal filtrate exhibited the most potent fraction (fraction 14–15), giving 94.6% egg mass hatching inhibition on the 5th day and a maximum nematicidal activity of 62% against second-stage juveniles after 48 h at 5000 mg/L. Gas chromatography coupled with mass spectrometry (GC-MS) analysis of this fraction revealed five major compounds, viz., 2-ethyl butyric acid, phenyl ethyl alcohol, benzoic acid, benzene acetic acid, and 3,5-Di-t-butylphenol. These biocompounds have potential biocontrol applications in agriculture, but further in vivo studies are warranted.
The complete plastid genome sequence of Chrysanthemum lucidum (Asteraceae): an endemic species of Ulleung Island of Korea

Abstract The characteristic of complete chloroplast (cp) genome sequence of Chrysanthemum lucidum, one of famous insular plant and an endemic to Ulleung Island of Korea, was firstly introduced in the present study. It was 150,985 bp and contained a large single copy region (82,786 bp) and a small single copy region (18,281 bp) which were separated by two inverted repeat regions (24,959 bp). In total, 131 genes were identified and they were consisted of 76 coding genes, eight rRNA genes, and 36 tRNA genes. Comparing to the previously reported Chrysanthemum indicum and C. x morifolium cp genomes, we found complete inversion of SSC region in this taxa. rpoC1 gene was pseudogenes due to 1 bp insertion of poly-A sequence in the 3′ of exon 2.
Genotype-environment interaction and stability of tef [Eragrostis tef (Zucc.) Trotter] varieties in Northeast Ethiopia

Analyzing Genotype-Environment interaction (GxE) is useful for exploring the opportunities and limiting the drawbacks of the effects. An investigation was conducted on 12 environments (six locations and two years) to study GxE and stability of 18 tef varieties, and to identify desirable environments. The experiment was laid in a randomized complete block design with three replications. The result of AMMI analysis of variance showed that tef grain yield was significantly (P < 0.001) affected by environments (E), genotypes (G) and GxE. Environment, G and GxE explained about 90.23%, 1.03% and 8.74% of the total sum of squares of treatments, respectively. The partitioning of the GxE by AMMI analysis showed that two of the Interaction Principal Component Axes (IPCAs) were highly significant (P < 0.001). The two IPCAs explained 66.06% of the total GxE in grain yield of the tef genotypes. AMMI1 showed that genotypes G and D had small interaction effects. Likewise, environments MR06 and KB07 had the highest interaction effects whereas SR06, KB06, JM06 and JM07 had smaller interaction effects. AMMI2 also showed that environments MR06, KB07 and CH07 exerted higher interaction effects; however, KB06, JM06 and JM07 exerted lower interaction effects. The GGE biplot identified three mega-environments: The first mega-environment is composed of environments Kobo, Jari and SR07 with genotype Tseday as a winner; genotype Ziquala represented the second mega-environment containing Jamma, Chefa and SR06; the third environment, made up of Mersa, was represented by genotype Asgori. Tseday was the most desirable variety; while Mersa was the least desirable environment.
Genetic diversity of Labyrinthula spp. in seagrass Zostera marina beds in the North Atlantic Ocean and the Baltic Sea

Seagrass wasting disease in the 1930s resulted in mass decline of seagrass Zostera marina in the Northern Atlantic Ocean. Labyrinthula zosterae is the potential pathogen of this disease that can lead to seagrass bed loss. This organism infects eelgrass’ leaf. Previous studies to identify the diversity of Labyrinthula spp. were based on culture method. This present study is the first study to use leaf samples for Labyrinthula molecular identification and explores diversity of the genus Labyrinthula. I investigated samples from six locations by cloning and Sanger sequencing of a 290 bp partial sequence of the 18S rDNA. Blast search against GenBank revealed that most sequences are 77-100% similar to L. zosterae, while some sequences from Wackerballig and Sandspollen were 84-94% matched Labyrinthula spp. None of that putative Labyrinthula spp. was grouped with known sequences from the database. There were seven OTUs generated. DNA extraction gave similar results for both tested extraction kits, a plant and a tissue kits. Nonetheless, the plant kit has more advantage due to its lower cost and time effort. In conclusion, this study shows undiscovered Labyrinthula spp. in the investigated eelgrass populations, second it shows that the method used in this study is suitable for further applications.
Morphological and Simple Sequence Repeat Analysis to Clarify the Diversity of Natural Lilium japonicum and L. auratum Hybrids in the Hybrid Zone of the Izu Peninsula, Japan

Lilium japonicum Thunb. which has pink or white-colored funnel-like flowers, is distributed in Kyushu, Shikoku, and the western part of Honshu, the main island of Japan. L. auratum Lindl. which has large white flowers with yellow central stripes and red spots, is distributed in the eastern part of Honshu. Natural hybridization of these two species has only been found on the Izu Peninsula of Honshu. However, details of the variation and hybridity of the interspecific hybrid population of these species on this peninsula remain unknown. In the present study, we conducted a morphological examination using 43, 21, and 90 individuals of L. japonicum, L. auratum, and the putative hybrid, respectively, from six, four, and ten populations of the Izu Peninsula, respectively. In addition, we performed simple sequence repeat (SSR) analysis using 47, 41, and 106 individuals of L. japonicum, L. auratum, and the putative hybrid, respectively, from six, four, and ten populations, respectively. Putative hybrid populations that resembled L. japonicum in morphology and SSR profile were found in the southern to eastern part of the peninsula, whereas those that resembled L. auratum and those exhibiting an intermediate morphology and SSR profile were found in the southern part of the peninsula. Large morphological variations exist in putative hybrid in the southern population, and interspecific hybridization has occurred in the southern and eastern populations. These results suggest that the center of natural hybridization is located in the southern part of the Izu Peninsula.
Identificação de procedências e progênies de Pinus maximinoi com potencial produtivo para madeira.

O objetivo desse trabalho foi estimar variabilidade genetica de dois ensaios de P. maximonoi para identificacao de matrizes com potencial produtivo para madeira na regiao de Ventania-PR. O delineamento experimento foi de blocos completos ao acaso, com 63 progenies area 1 e 77 progenies na area 2 procedentes de oito procedencias, nove repeticoes, seis plantas por parcela, espacamento de 3 x 3 metros. Os caracteres avaliados foram: diâmetro a 1,30 m do solo (DAP, cm), altura total (ALT, m) e volume (VOL, m3.tree-1). As estimativas dos parâmetros geneticos e o ganho na selecao foram estimados com base no metodo REML/BLUP. Diferencas significativas (p<0,01) foram observadas entre procedencias nos dois locais. Houve diferencas significativas entre progenies para os caracteres ALT, DAP e VOL somente para as procedentes de Dulce N. de Colpan (Honduras) e San Jeronimo de Oaxaca (Guatemala) na area 1 e Tapiquil (Honduras) e Valle de Ageles (Honduras) (DAP e VOL) na area 2. Na analise entre procedencias os baixos coeficientes de variacao genetica, herdabilidade aditivos e herdabilidade media de progenies mostram baixo controle genetico para os caracteres. As procedencias de P. maximinoi apresentaram bom crescimento e desempenho em volume na regiao de Ventania-PR. As procedencias de P. maximinoi devem ser consideradas para plantios comerciais e o estabelecimento de areas de producao de sementes para essa especie. Dentre as procedencias testadas, San Jeronimo (Mexico) teve as maiores taxas de incremento em volume.
A survey on application of machine learning to manage the virtual machines in cloud computing

Virtual machine (VM) management is a fundamental challenge in the cloud datacenter, as it requires not only scheduling and placement, but also optimization of the method to maintain the energy cost and service quality. This paper reviews the different areas of literature that deal with the resource utilization prediction, VM migration, VM placement and the selection of physical machines (PMs) for hosting the VMs. The main features of VM management policies were also examined using a comparative analysis of the current policies. Many research works include Machine Learning (ML) for detecting the PM overloading, the selection of VMs from over-utilized PM and VM placement as the main activities. This article aims to identify and classify research done in the area of scheduling and placement of VMs using the ML with resource utilization history. Energy efficiency, VM migration counts and Service quality were the key performance parameters that were used to assess the performance of the cloud datacenter.