Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilities of Failures in Construction Works Completion in Governmental Institutions, an Analysis on the Causing Factors

There are always goods/services procurements each year in governmental institutions, both central and local governments. However, there are often failures in the completion, causing the work progresses slowly, the quality is not well-controlled, the contract is terminated, and some works are even abandoned. The research‟s object is the probabilities of failures in construction works in governmental institutions, while the respondents were officers of governmental institutions involved or once involved or understanding participations of all parties involved in the construction works. Their involvements were in each of work stages, starting from preparing procurement, contacting procurement committee, making contract, planning, executing, controlling, and completing the work. Competence of the Commitment Making Official (CMO/PPK), technical skills of the contractors, planners, supervisors, and technical teams were factors considered to be playing a role in the failures. In addition, however, managerial skills of the administrators, natural/nontechnical conditions, post of the CMO in the organisation, position issues, and period of work were also researched as the other non-ignorable factors that may cause the failures. The data were collected from questionnaires distributed to some selected respondents from various governmental institutions in some provinces in Indonesia. Furthemore, using probit model method, the data were processed and analysed. According to the results, only managerial skills of the administrator, technical skills of the contractor and supervising consultant, skills of the Procurement Service Unit (PSU/ULP) committee, position and period of work of the construction executing team had influence on the probabilities of failures in the construction works completion, while the other factors did not have any significant influence.
Passiflora ligularis leaf ultrasound-assisted extraction in the optimization of flavonoid content and enhancement of hypoglycemic activity

Among the different metabolites found in the Passiflora species, flavonoids have been related to some of the therapeutic effects of these plants. In the case of Passiflora ligularis, the presence of these metabolites has been related to a promising hypoglycemic effect. This study aimed to optimize the total flavonoid content of P. ligularis leaf extract to improve its therapeutic activity. The effect of three variables (ethanol percentage, temperature, and time) on the ultrasound-assisted flavonoid extraction was evaluated by means of response surface methodology. The effect of increasing the flavonoid content on the extract activity was evaluated with an in vitro antiglycation assay and an in vivo glucose tolerance test in mice. The optimal extraction conditions were 63% ethanol, 70oC, and 33 minutes. The predicted maximum flavonoid yield (57.77 mg-equivalent isoquercetin/g dry extract) correlated with the experimental value (59.76 ± 1.90 mg-equivalent isoquercetin/g dry extract) and the extraction process proved to be highly reproducible, suggesting that ultrasound-assisted extraction is a simple, inexpensive, and effective alternative technique for the extraction of flavonoids in Passiflora species. Moreover, the optimized extract exhibited the highest antiglycation activity against all the experimental design treatments and showed an enhanced hypoglycemic effect in mice compared to a traditionally extracted beverage.
Variability, correlation and path analysis in F2 population of cross between hot pepper and bell pepper

The extent of genetic variability, heritability, genetic advance as percent of mean and correlation coefficients in respect of 12 quantitative characters in the population of cross between Byadgi chilli and bell pepper were studied. High phenotypic and genotypic coefficient of variations for number of fruits per plant (68.02 and 52.16) reported, followed by dry fruit yield per plant, fruit volume, number of primary branches, number of secondary branches, plant height and fruit surface area. High heritability and genetic advance as percent of mean was observed for fruit yield per plant, average fruit weight, pericarp weight per fruit, seed weight per fruit, which could be improved by simple selection. A significant positive correlation of economic traits like number of fruits per plant, fruit weight and fruit lengths with fruit yield per plant was recorded suggesting that selection for these characters could lead to improvement in yield. Path analysis revealed that number of fruits per plant had maximum direct effects on fruit yield followed by fruit length, fruit diameter and pericarp weight. Thus emphasis should be given on these characters to improve yield potential. The traits such as fruit yield per plant, number of fruits per plant, fruit weight are important yield contributing characters and deserve due weightage, while formulating selection strategies for improvement of chilli. As high genetic variability revealed in F2 population studied, this can be effectively utilized for improving yield and component traits.
Concurrent validity of a developed accelerometry-based device for postural sway assessment

Postural control is one factor related to falls. Many instruments are available to objectively evaluate postural control performance. However, feasibility and applicability is limited by setting and financial restraints. Therefore, the purpose of this study was to assess the concurrent validity between a developed accelerometry-based sway meter and 3D-motion analysis system. Twenty healthy volunteers participated in this study. Postural sway during quiet stance, and leaning (forward, backward, left and right) were collected using a 3D-motion analysis system and the developed accelerometry-based device simultaneously. Pearson’s product correlation coefficient was used to determine the relationship between the two instruments. Significant correlations were found between center of mass sway angle measured by 3D-motion system and the developed sway meter. These findings and the affordable sway meter device may provide support for the use of the accelerometry sway meter in evaluating sway when standing both static and dynamic conditions.
Quest for the Golden Approach: An Experimental Evaluation of Duplicate Crowdtesting Reports Detection

Background: Given the invisibility and unpredictability of distributed crowdtesting processes, there is a large number of duplicate reports, and detecting these duplicate reports is an important task to help save testing effort. Although, many approaches have been proposed to automatically detect the duplicates, the comparison among them and the practical guidelines to adopt these approaches in crowdtesting remain vague. Aims: We aim at conducting the first experimental evaluation of the commonly-used and state-of-the-art approaches for duplicate detection in crowdtesting reports, and exploring which is the golden approach. Method: We begin with a systematic review of approaches for duplicate detection, and select ten state-of-the-art approaches for our experimental evaluation. We conduct duplicate detection with each approach on 414 crowdtesting projects with 59,289 reports collected from one of the largest crowdtesting platforms. Results: Machine learning based approach, i.e., ML-REP, and deep learning based approach, i.e., DL-BiMPM, are the best two approaches for duplicate reports detection in crowdtesting, while the later one is more sensitive to the size of training data and more time-consuming for model training and prediction. Conclusions: This paper provides new insights and guidelines to select appropriate duplicate detection techniques for duplicate crowdtesting reports detection.
KERAGAMAN GENETIK AYAM KAMPUNG BERDASARKAN ANALISIS PENANDA DAERAH D-LOOP MITOKONDRIA DNA

SARTIKA, T. , D. DURYADI, S. S. MANSJOER, and B. GUNAWAN. 2000. Genetic diversity of native chicken based on analysis of D-Loop mtDNA marker. Jurnal Ilmu Ternak dan Veteriner 5(2): 100-106. Genetic diversity of base selection population of native chicken (Gallus gallus domesticus) at Research Institute for Animal Production was carried out using control region/D-loop mtDNA marker. The base population of native chicken was selected from subpopulation at Cianjur, Jatiwangi, Depok, Bogor I, and Bogor 2. Samples from each population was 10 heads and 2 samples Green Jungle Fowl (Gallus various) from East Java as out Group samples. Two primers binding conserved tRNA Phenylalanine gene and tRNA Glutamine gene were DNA Heavy stranded HI255 (5'-CATCTTGGCATCTTCAGTGCC-3') and DNA Light stranded Ll6750 (5'-AGGACTACGGCTTGAAAAGC-3') was used to amplify D-Ioop mtDNA chicken. PCR-RFLP methods with 6 restriction enzymes 4 cutter such as, Alul (AG↓CT), Hpall (C↓CGG), Mbol (↓GATC), Rsal (GT↓AC), NlaIII (CATG↓) and HaeIII (GG↓CC) were used to detect polymorphism within and between subpopulation. Result of experiment show that mtDNA which was amplified by PCR was 1320 bp, consist of 1227 bp control region/D-loop, 45 bp tRNA Glutamine gene and 48 bp tRNA Phenylalananine gene. PCR product which were digested from 6 endonucleases enzyme show that native chicken within and between population was monomorphic and if its compare with Green Jungle Fowl was polymorphic.
Sumorilação e nedilação de proteínas em Schistosoma mansoni.

xvi 1. INTRODUÇÃO . 17 1.1. Esquistossomose . 18 1.2. Ciclo evolutivo do S. mansoni . 19 1.3. Regulação da expressão gênica . 23 1.4. Modificação pós-traducional dependente de proteínas . 26 1.5. Small Ubiquitin Modifier (SUMO) . 30 1.6. Neural precursor cell expressed developmentally downregulated protein 8 (NEDD8) . 35 1.7. COP9 signalossoma (CSN) . 38 1.8. Interface entre as vias de modificação dependente de UBLs . 39 1.9. Modificação pós-traducional dependente de Ubls e estresse . 41 2.0. Modificação pós-traducional dependente de Ubls em S. mansoni . 43 2.1. Mecanismos de respostas ao estresse em S. mansoni . 44 2. OBJETIVOS . 47 2.1. Objetivo Geral . 48 3. CAPÍTULO I. SUMO-E3 LIGASES: PIAS E RANBP2 . 49 4. CAPÍTULO II. ENZIMAS DESUMORILADORAS: SENPs . 66 5. CAPÍTULO III. VIA DE NEDILAÇÃO . 75 6. CAPÍTULO IV. COMPLEXO COP9 SIGNALOSSOMA . 86 7. CAPÍTULO V. EFEITO DO ESTRESSE NAS VIAS DE SUMORILAÇÃO E NEDILAÇÃO . 97 8. DISCUSSÃO . 116 9. CONCLUSÃO . 122 10. ATIVIDADES DESENVOLVIDAS . 124 11. PERSPECTIVAS . 127 12. BIBLIOGRAFIA . 132 13. ANEXOS . 150
Extended SEIQR type model for COVID-19 epidemic and data analysis

An extended SEIQR type model is considered in order to model the COVID-19 epidemic. It contains the classes of susceptible individuals, exposed, infected symptomatic and asymptomatic, quarantined, hospitalized and recovered. The basic reproduction number and the final size of epidemic are determined. The model is used to fit available data for some European countries. A more detailed model with two different subclasses of susceptible individuals is introduced in order to study the influence of social interaction on the disease progression. The coefficient of social interaction $K$ characterizes the level of social contacts in comparison with complete lockdown (K=0) and the absence of lockdown (K=1). The fitting of data shows that the actual level of this coefficient in some European countries is about 0.1, characterizing a slow disease progression. A slight increase of this value in the autumn can lead to a strong epidemic burst.
Analgesic and anti-inflammatory effects of Cyphostemma vogelii (Hook. f.) Desc. root extract in mice

Cyphostemma vogelii (family: Vitaceae) is a herbaceous plant which grows in Obukpa town in South Eastern Nigeria. C. vogelii is said to be generally medicinal though no specific medicinal activity was mentioned in the literature for this plant. The analgesic effect of C. vogelii was evaluated using acetic acid-induced writhing and formalin-induced nociception tests. The extract was also screened for antiinflammatory activity using carrageenan-induced and kaolin-carrageenan-induced paw edema tests. C. vogelii extract dose dependently inhibited acetic acid-induced pain in mice. The extract at 200 and 400 mg/kg significantly inhibited inflammatory and neurogenic pain induced by formalin. The effects of 200 mg/kg on formalin induced pain were similar to those of aspirin, while 400 mg/kg produced more inhibitory effects. At 2, 3 and 5 h post carrageenan injection, 200 and 400 mg/kg extract significantly inhibited paw edema. The extract dose dependently suppressed kaolin-carrageenan-induced edema from 3 h post treatment for up to 24 h. The effect of 400 mg/kg on kaolin-carrageenan-induced edema was similar to that of aspirin, while 100 mg/kg showed the least activity. The data obtained from this study showed that the methanol extract of C. vogelii exhibited mild analgesic activity as well as antiinflammatory activity. Keywords : Analgesic, anti-inflammatory, mice, Cyphostemma vogelii , nociception African Journal of Biotechnology Vol. 12(17), pp. 2288-2292
Development of a statistical framework for mass spectrometry data analysis in untargeted Metabolomics studies

A central objective in the analysis of mass spectrometry-based untargeted Metabolomics data is the detection of intensity patterns that differ between experimental conditions and the identification of underlying metabolites and biochemical processes. In this context, the identification of metabolites is a major bottleneck and needs to be guided by expert knowledge and tools for explorative data analysis. The integration of data sets from other omics platforms, e.g. DNA microarray-based Transcriptomics, can thereby provide valuable hints and support the reconstruction of related metabolic pathways, which then form the biochemical context for metabolite identification. In this work, a statistical framework and user interfaces for exploratory evaluation of mass spectrometry-based non-targeted Metabolomics data in combination with data sets from other omics platforms are introduced. The developed methods and tools were combined in the highly interactive MarVis-Suite software. The MarVis-Filter interface includes functions for the adduct and isotope correction of mass spectrometry data, molecular formula prediction, statistical ranking, filtering, and combination of cross-omics data sets. Within MarVis-Cluster, intensity profiles associated with ion species or microarray spots (features) in filtered and combined data sets can be clustered, visualized, interactively inspected and labeled. By means of MarVis-Pathway, data set features may be annotated in the context of organism-specific metabolic pathways. For statistical analysis, which forms a counterweight to the highly interactive and selective MarVis workflow, an extensive framework for meta-analysis of multi-omics data sets based on pathway enrichment analysis was developed. The methods and tools were successfully applied to several liquid chromatography/mass spectrometry data sets in combination with DNA microarray data in the context of plant wounding. The integration of Transcriptomics data thereby significantly supported the analysis and interpretation of non-targeted Metabolomics data sets.
Identification of microrna families expressed in sugarcane leaves subjected to drought stress and the targets thereof.

The first three authors contributed equally to this paper. MicroRNA families are important regulators of plant resistance to diverse stressors, but the miRNA families expressed in response to drought, and the levels thereof, in sugarcane (an important commercial source of both sugar and biofuel) remain poorly understood. In the present study, we determined the expression profile of miRNA families synthesized by leaves of the drought-resistant cultivar ROC22 stressed by addition of PEG to the growth substrate. Totals of 23 conserved miRNA families and 34 new miRNA families were identified, and 438 putative target genes of 44 miRNA families were described. Expression analysis revealed that 11 miRNA families were differentially expressed in control and drought-exposed plants. Of these, nine families were up-regulated and two down-regulated. The potential targets of the 11 miRNA families were genes associated with plant growth and stress resistance, specifically SPBP, MYB, the AGO1-like gene, NCBP, BCP, CPI, and LSG. With the exceptions of SPBP, NCBP and BCP, the other genes were down-regulated in response to drought stress. Our preliminary identification of 11 relevant miRNA families expressed by ROC22, and their targets, suggest that these miRNA families may regulate the response to drought stress and forms a basis for planned future work. The other new miRNA families identified, along with their targets, may exert novel effects on various metabolic pathways relevant to sugarcane growth and development.
Deterministic Replacement Path Covering

In this article, we provide a unified and simplified approach to derandomize central results in the area of fault-tolerant graph algorithms. Given a graph $G$, a vertex pair $(s,t) \in V(G)\times V(G)$, and a set of edge faults $F \subseteq E(G)$, a replacement path $P(s,t,F)$ is an $s$-$t$ shortest path in $G \setminus F$. For integer parameters $L,f$, a replacement path covering (RPC) is a collection of subgraphs of $G$, denoted by $\mathcal{G}_{L,f}=\{G_1,\ldots, G_r \}$, such that for every set $F$ of at most $f$ faults (i.e., $|F|\le f$) and every replacement path $P(s,t,F)$ of at most $L$ edges, there exists a subgraph $G_i\in \mathcal{G}_{L,f}$ that contains all the edges of $P$ and does not contain any of the edges of $F$. The covering value of the RPC $\mathcal{G}_{L,f}$ is then defined to be the number of subgraphs in $\mathcal{G}_{L,f}$. We present efficient deterministic constructions of $(L,f)$-RPCs whose covering values almost match the randomized ones, for a wide range of parameters. Our time and value bounds improve considerably over the previous construction of Parter (DISC 2019). We also provide an almost matching lower bound for the value of these coverings. A key application of our above deterministic constructions is the derandomization of the algebraic construction of the distance sensitivity oracle by Weimann and Yuster (FOCS 2010). The preprocessing and query time of the our deterministic algorithm nearly match the randomized bounds. This resolves the open problem of Alon, Chechik and Cohen (ICALP 2019).
Sampling Signals on Graphs: From Theory to Applications

The study of sampling signals on graphs, with the goal of building an analog of sampling for standard signals in the time and spatial domains, has attracted considerable attention recently. Beyond adding to the growing theory on graph signal processing (GSP), sampling on graphs has various promising applications. In this article, we review the current progress on sampling over graphs, focusing on theory and potential applications.
Gravitational formfactors of the $ \rho $ meson in QCD sum rules.

By using the quark part of the energy-momentum tensor current, the gravitational formfactors of the $ \rho $ meson are calculated within the light-cone sum rules method. In the considered version, the energy-momentum tensor current is not conserved and as a result, there appear nine formfactors, six (three) of which correspond to the conservation (nonconservation) of the energy-momentum tensor current. We also compare our results with the one existing in the literature.
Could the Migration of Jupiter Have Accelerated the Atmospheric Evolution of Venus?

In the study of planetary habitability and terrestrial atmospheric evolution, the divergence of surface conditions for Venus and Earth remains an area of active research. Among the intrinsic and external influences on the Venusian climate history are orbital changes due to giant planet migration that have both variable incident flux and tidal heating consequences. Here, we present the results of a study that explores the effect of Jupiter’s location on the orbital parameters of Venus and subsequent potential water-loss scenarios. Our dynamical simulations show that various scenarios of Jovian migration could have resulted in orbital eccentricities for Venus as high as 0.31. We quantify the implications of the increased eccentricity, including tidal energy, surface energy flux, and the variable insolation flux expected from the faint young Sun. The tidal circularization timescale calculations demonstrate that a relatively high tidal dissipation factor is required to reduce the eccentricity of Venus to the present value, which implies a high initial water inventory. We further estimate the consequences of high orbital eccentricity on water loss, and estimate that the water-loss rate may have increased by at least ∼5% compared with the circular orbit case as a result of orbital forcing. We argue that these eccentricity variations for the young Venus may have accelerated the atmospheric evolution of Venus toward the inevitable collapse of the atmosphere into a runaway greenhouse state. The presence of giant planets in exoplanetary systems may likewise increase the expected rate of Venus analogs in those systems.
Modeling Prosodic Phrasing With Multi-Task Learning in Tacotron-Based TTS

Tacotron-based end-to-end speech synthesis has shown remarkable voice quality. However, the rendering of prosody in the synthesized speech remains to be improved, especially for long sentences, where prosodic phrasing errors can occur frequently. In this letter, we extend the Tacotron-based speech synthesis framework to explicitly model the prosodic phrase breaks. We propose a multi-task learning scheme for Tacotron training, that optimizes the system to predict both Mel spectrum and phrase breaks. To our best knowledge, this is the first implementation of multi-task learning for Tacotron based TTS with a prosodic phrasing model. Experiments show that our proposed training scheme consistently improves the voice quality for both Chinese and Mongolian systems.
Modelling Regional Crime Risk using Directed Graph of Check-ins

The location-based social network, Foursquare, reflects the human activities of a city. The mobility dynamics inferred from Foursquare helps us understanding urban social events like crime In this paper, we propose a directed graph from the aggregated movement between regions using Foursquare data. We derive region risk factor from the movement direction, quantity and crime history in different periods of the day. Later, we propose a new set of features, DIrected graph Flow FEatuRes (DIFFER) which are associated with region risk factor. The reliable correlations between DIFFER and crime count are observed. We verify the effectiveness of the DIFFER in monthly crime count using Linear, XGBoost, and Random Forest regression in two cities, Chicago and New York City.
Prediction of the Properties of the Rare-Earth Magnets 
Ce2Fe17−xCoxCN
: A Combined Machine-Learning and 
Ab Initio
 Study

We employ a combination of machine learning and first-principles calculations to predict magnetic properties of rare-earth lean magnets. For this purpose, based on training set constructed out of experimental data, the machine is trained to make predictions on magnetic transition temperature (Tc), largeness of saturation magnetization ({\mu}0Ms), and nature of the magnetocrystalline anisotropy (Ku). Subsequently, the quantitative values of {\mu}0Ms and Ku of the yet-to-be synthesized compounds, screened by machine learning, are calculated by first-principles density functional theory. The applicability of the proposed technique of combined machine learning and first-principles calculations is demonstrated on 2-17-X magnets, Ce2Fe17-xCoxCN. Further to this study, we explore stability of the proposed compounds by calculating vacancy formation energy of small atom interstitials (N/C). Our study indicates a number of compounds in the proposed family, offers the possibility to become solution of cheap, and efficient permanent magnet.