Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Congo Red agar for detection of Streptococcus dysgalactiae isolated from diseased fish.

Summary The strong clinical similarity between Lancefield group C Streptococcus dysgalactiae subsp. dysgalactiae (GCSD) and Lactococcus garvieae infections, characterized by development of necrotic lesions in the caudal peduncle of infected fish, has hindered differentiation of these two strains, making rapid and accurate diagnosis of diseased fish in fish farms difficult. GCSD from diseased fish were presumptively identified and isolated using Todd-Hewitt agar containing 30 μg ml−1 of Congo Red dye (TH-CR). TH-CR agar was also used to detect and presumptively identify the GCSD obtained from artificially or naturally infected fish. Orange GCSD colonies distinct from the L. garvieae colonies were observed on the TH-CR agar; thus, TH-CR agar can be used to detect and identify GCSD isolated from infected fish.
Determinants of Intellectual Capital Performance in Indonesian Manufacturing Companies

In the last few decades, the world has been undergoing rapid advancements in science and technology that influence global economic development. A change from industrial to science-based economy has also embarked. Science holds a prominent role in the utilization of intangible resources in the form of intellectual capital that should be disclosed to investors. This research is aimed at investigating whether intellectual capital performance is influenced by firm size, age, profitability, and ownership. This research was a quantitative study from secondary data and the VAICTM model. 152 manufacturing companies listed on the Indonesia Stock Exchange in the period 2014–2017 were chosen as the sample. Two analysis methods were employed, namely descriptive analysis and panel data regression analysis. Results indicated that firm age had a significant effect on intellectual capital performance, while firm profitability had a positive effect on intellectual capital performance. However, firm size and firm ownership had no significant effect on intellectual capital performance. Many of the manufacturing companies in Indonesia have yet to focus on intellectual-capital-based business. It is thus recommended that manufacturing companies in Indonesia increase their focus on intellectual capital.
Response of pea (Pisum sativum L.) to mepiquat chloride under varying application doses and stages

Grown as a monoculture, peas (Pisum sativum L.) exhibit severe lodging after flowering and lodging causes yield reductions considerable. This study was conducted to investigate the effects of dose (untreated, 25, 50, 75 and 100 g a.i. ha -1 ) and stage (late vegetative, early blooming and early pod filling) of mepiquat chloride (MC) application on the growth, lodging control, seed yield and yield parameters of pea (Pisum sativum L.) under field conditions in Erzurum, Turkey in 2002 and 2003. Application doses of 25, 50, 75 and 100 g a.i. ha -1 significantly reduced stem height by 5.3 %, 7.2 %, 7.5 % and 6.4 % and increased stem width by 7.5 %, 12.7 %, 12.3 % and 15.7 % respectively, when compared with the untreated control, and thereby reduced the tendency of the crop to lodging. Increases of the seed yield under different application doses of MC ranged between 13.7 % and 20.1 % over the untreated control. However, in all parameters investigated, except for stem width, higher application doses of MC gave no clear advantages compared with the application dose of 25 g a.i. ha -1 . Seed yield was also significantly influenced by application stage of MC and application at early blooming stage of crop, MC significantly increased seed yield by 11.4 % and 10.2 % when compared with the late vegetative and the early pod filling stages respectively. Furthermore, the interaction of application dose and stage was significant, and spraying of pea plants with 25 g a.i. -ha -1 MC at early blooming stage has the most beneficial effects on the characters evaluated.
The Nunavut Hansard Inuktitut–English Parallel Corpus 3.0 with Preliminary Machine Translation Results

The Inuktitut language, a member of the Inuit-Yupik-Unangan language family, is spoken across Arctic Canada and noted for its morphological complexity. It is an official language of two territories, Nunavut and the Northwest Territories, and has recognition in additional regions. This paper describes a newly released sentence-aligned Inuktitut–English corpus based on the proceedings of the Legislative Assembly of Nunavut, covering sessions from April 1999 to June 2017. With approximately 1.3 million aligned sentence pairs, this is, to our knowledge, the largest parallel corpus of a polysynthetic language or an Indigenous language of the Americas released to date. The paper describes the alignment methodology used, the evaluation of the alignments, and preliminary experiments on statistical and neural machine translation (SMT and NMT) between Inuktitut and English, in both directions.
Expedience of Investing in the Intellectual Potential of an Enterprise Using the Example of PJSC Gazprom

One of the most important enterprise resources, ensuring its competitive advantage in the Russian and international markets, is its personnel with their knowledge, skills, smart ideas, effectively developing innovative projects and implementing them. Professionals are able to significantly increase the value and income of the company, raise its position. Therefore, the need to invest in the intellectual potential of the company is relevant. To study this issue, a regression analysis and an econometric modeling of the company's competitiveness were carried out through the dependence of its profit on some parameters characterizing the intellectual potential of the enterprise, using the example of Gazprom Corporation. The Eviews10 application package was used. To that end, the works of Russian and foreign scientists were studied, the statistical data of the Annual reports on the activities of PJSC Gazprom for 2000-2018 were used. As a result of the study, it was found that the intellectual potential of the enterprise increases the value of the organization and its competitiveness. The resulting econometric model provides an opportunity to forecast in the short term. The WEF data in Davos for 2017-2019 indicate that Russia ranks 43 in the global competitiveness rating and 25 in terms of innovation activity. Russia has a chance to get into the Top 10 in terms of innovation development, however, this will require significant cash injections and high-quality human capital.
Large impact of tiny model domain shifts for the Pentecost 2014 mesoscale convective system over Germany

Abstract. The mesoscale convective system (MCS) that affected Germany at Pentecost 2014 (9 June 2014) was one of the most severe for decades. However, the predictability of this system was very low as the operational deterministic and ensemble prediction systems completely failed to predict the event with more than a 12 h lead time. We present hindcasts of the event using the COnsortium for Small-scale MOdeling (COSMO) model at a convection-permitting (2.8 km) resolution on a large ( 1668 km ×1807 km) domain. Using this large domain allowed us to successfully simulate the whole life cycle of the system originating from the French Atlantic coast. However, even with the large domain, the predictability of the MCS is low. Tiny changes to the model domain produced large changes in the MCS, removing it completely from some simulations. To demonstrate this we systematically shifted the model domain by just one grid point in eight different directions, from which three did not simulate any convection over Germany. Our analysis shows that there were no important differences in domain-averaged initial conditions or in the preconvective environment ahead of the convective system. The main reason that one-third of these seemingly identical initial conditions fail to produce any convection over Germany seems to be the proximity of the track of the initial convective system to the coast and colder sea surface. The COSMO model simulates small horizontal displacements of the precursors of the MCS which then determine if the cells dissipate close to the sea or reach a favorable area for convective development over land and further evolve into an MCS. This study demonstrates the potentially huge impact of tiny model domain shifts on forecasting convective processes in this case, which suggests that the sensitivity to similarly small initial-condition perturbations could be a helpful indicator of days with low predictability and should be evaluated across other cases, models, and weather regimes.
Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV–visible spectrometers during CINDI-2

Abstract. In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.
Impact of Delayed Completion of Previously Initiated Therapy and Provider Type on Outcomes of Root Canal Treatment

IMPACT OF DELAYED COMPLETION OF PREVIOUSLY INITIATED THERAPY AND PROVIDER TYPE ON OUTCOMES OF ROOT CANAL TREATMENT Igor Sulim, D.D.S. Marquette University, 2020 Objective: The primary purpose of this study was to determine if the period of time between previously initiated therapy and the completion of non-surgical root canal treatment (NSRCT) influences long-term outcomes. The secondary purpose of this study was to determine if the provider type influences long-term outcomes in instances where NSRCT has been previously initiated. Materials/Methods: Enrollment and claims data from Delta Dental of Wisconsin from 2002-2014 was analyzed. Teeth that received NSRCT within 6 months after completion of pulpal debridement or pulpotomy procedures (identified by Codes of Dental Procedures and Nomenclature) and within a continuous insurance coverage period were included. Teeth that did not receive definitive restorations within 180 days following completion of NSRCT were excluded. Teeth were followed from the time of treatment to the presence of a CDT code representing untoward events, which include retreatment, apicoectomy, or extraction. The impact of tooth location, age at time of NSRCT completion, and provider type on the outcome was also examined using Univariate and Multivariable Cox proportional hazards models. A total of 7,488 NSRCTs were included in the analysis. Results: No statistically significant difference was found among the varying time intervals between initiation and completion of NSRCT. Molar teeth were associated with a greater risk of an untoward event than anterior teeth with an adjusted hazard ratio of 1.52 (p<0.029). An increase in the risk of failure was observed in teeth from patients that were 55 and older with an adjusted hazard ratio 2.15 (p<0.001). A significantly lower adjusted hazard ratio of 0.68 (p<0.001) was observed when treatment was initiated by a general dentist and completed by an endodontist when compared to treatment that was both initiated and completed by a general dentist. Conclusion: Delayed completion of NSRCT after previously initiated therapy was not associated with unfavorable outcomes. Improved outcomes were noted when previously initiated therapy was completed by an endodontist.
Interpreting regulatory variants with predictive models

Many human diseases are caused by genetic variants. Precision medicine requires understanding the genetic basis of diseases. With the advances of the next-generation sequencing techniques, the whole genome can be sequenced at a low cost. Large cohorts of individuals are now sequenced, and millions of variants have been identified. However, it remains challenging to interpret most of them. Even though statistical methods have been developed to associate variants with different phenotypes including diseases, precisely locating the causal variant is difficult. On the other hand, tremendous high throughput genomics data are now publicly available; new assays keep being developed to better probe functions of genetic sequences. These data systematically covers almost all crucial biological processes, like protein DNA interaction, protein RNA interaction, splicing, and RNA degradation. They provide unique opportunities to train machine learning models to predict the functional impact of variants on specific biological processes and also overall variant pathogenicity. Here, I developed machine learning models predicting two major gene expression steps solely from sequences: RNA splicing and degradation. Specifically, this thesis contributes to variant interpretation in threefold: First, I systematically investigated sequence elements regulating mRNA stability in the model organism Saccharomyces cerevisiae, for which we have high-quality genome-wide RNA half-life measured. A model integrating all sequence elements can explain 59% of mRNA half-life variation across genes. The analysis quantified the major role of codon usage in determining mRNA stability and revealed a new destabilizing motif ATATTC. Variants on 3′ UTR motifs and upstream AUG codon (uAUG) have the largest effect on mRNA stability. Furthermore, the corresponding RNA degradation pathways through which different sequence elements affect mRNA stability were characterized. Second, I developed MMSplice, a modular deep learning framework to predict effect of genetic variants on splicing in human cells. MMSplice outperformed state-of-the-art models and was the winning model of the 5th Critical Assessment of Genome Interpretation (CAGI) exon-skipping competition. MMSplice consists of modular models to score splicing-relevant regions. The framework can score variant effect on different splicing patterns, including exon skipping, alternative splice sites as well as intron retention. Moreover, MMSplice improved the prediction accuracy of pathogenicity of variants located near splice sites. Third, I implemented MMSplice as a python package that can be directly applied to score variants from a Variant Call Format (VCF) file, enabling it to be easily incorporated into variant interpreting pipelines along with other tools. Moreover, I helped develop Kipoi, a platform to deposit and reuse predictive models in genomics.
Responses to pH of nine fishes and one shrimp native to New Zealand freshwaters

Abstract The pH values preferred and avoided by adult stages of inanga (Galaxias maculatus), common bully (Gobiomorphus cotidianus), common smelt (Retropinna retropinna), and redfinned bully (G. huttoni), were determined in a gradient tank (pH ranges of 3.2–11.2). Juvenile stages of inanga, common bully, shortjawed kokopu (Galaxias postvectus), koaro (G. brevipinnis), banded kokopu (G. fasciatus), shortfinned (Anguilla australis) and longfinned (A. dieffenbachii) elvers and glass eels, as well as freshwater shrimp (Paratya curvirostris) were also tested. Most species were found to have pH preferences and all except inanga avoided pH values of above c. 9.5. Adult fish showed stronger preferences than juveniles. An avoidance of pH values below 6.5 was apparent in most species except shortfinned elvers, koaro, and banded kokopu. Results indicate that the range of pH encountered in lowland streams are unlikely to have a major impact on the distribution of most New Zealand native freshwater fish.
WHO EMRO | Malnutrition and food insecurity in child labourers in Sindh, Pakistan: a cross-sectional study

Background: Child labour is common in lowand middle-income countries. Although child labour is widespread in Pakistan, no data are available on the health of child labourers. Aims: This study aimed to assess the food security, food intake and nutritional status of child labourers aged 5–14 years working in lower Sindh, Pakistan. Methods: Child labourers aged 5–14 years working in agriculture, manufacturing industry, hotels and restaurants, domestic work and migrant child labourers working in vegetable markets were recruited using a respondent-driven sampling technique. Sociodemographic and nutrition information was obtained by an interviewer questionnaire. The children’s height and weight were measured to assess stunting (height-for-age z scores less than –2) and wasting (weight-for-height z scores less than –2). Results: A total of 634 child labourers were included: 184 worked in agriculture, 120 in industry, 67 in hotels and restaurants, 63 in domestic work and 200 were migrant child labourers. Overall, 15.5% of the children were stunted and 30.0% were wasted. The prevalence of stunting was highest in children working in agriculture (27.2%) and the prevalence of wasting was highest in migrant child workers (35.0%). About half the children (51.1%) were suffering from food insecurity. Food inadequacy was mainly in consumption of vegetables/potatoes (98% of the children had inadequate intake), legumes (97%), fruits (96%), meat/ poultry (95%) and milk/dairy products (82%).
Cellular and molecular approaches to understanding primary adhesion in Enteromorpha: an overview

The attachment of motile spores of the green alga Enteromorpha to the substratum is an active process involving an irreversible commitment to adhesion and the secretion of an adhesive. This paper provides an overview of the spore adhesion processes and outlines the results of an experimental approach towards the molecular characterisation of the adhesive, based on the use of monoclonal antibody (mAb) technology. Hybridomas were produced to settled spores displaying secreted adhesive. Candidates producing mAbs to putative adhesive were selected using a range of criteria based on cellular localisation, time of secretion and functional inhibition of adhesion. MAb Ent 6 immunolabelled fibrillar material which was secreted during the early stages of adhesion and low (nM) concentrations of this mAb, or its F(ab)2 fragments, strongly inhibited the attachment of zoospores. A related antibody (Ent 1) also labelled the spore adhesive apparatus, but the antigen appeared to be secreted later during the adhesion process and was predominantly associated with the developing cell wall. Ent 1 also inhibited settlement in spore adhesion assays but the effect was most pronounced at later time points which suggests that this antigen does not have a role in the earliest stages of adhesion. Immunolocalisation showed that both antigens were absent from the cytoplasm or organelles of vegetative tissue but labelled the vegetative cell wall, suggesting a relationship between cell wall components and materials involved in primary adhesion. Both mAbs labelled the Golgi region of settled spores, suggesting continued synthesis of both antigens after adhesion. Both mAbs recognised a 110 kDa N‐linked polydisperse and heterogeneous glycoprotein in extracts of swimming spores under denaturing conditions. In native form the antigens behaved as high molecular weight aggregates (Mr>1.3 × 106). The antigens became progressively insoluble after zoospore attachment. Taken together, the data suggest that the two antibodies recognise closely related, polydisperse, self‐aggregating cell wall glycoproteins in which there is some structural variation to suit alternative roles in primary adhesion and cell wall formation. The two mAbs Ent 1 and Ent 6 partially discriminate between these structural and functional variants. A model for zoospore adhesion is discussed in which adhesion is viewed as an extension of cell wall synthesis, with cross‐links between glycoproteins and other cell wall matrix components providing a strong physical continuum between the cell and the adhesive at the substratum interface.
Running head: EXAMINING FACTORS EXAMINING FACTORS ASSOCIATED WITH PHYSICAL ACTIVITY DURING CARDIAC REHABILIATION

Recurrent myocardial infarctions (MIs) account for a third of the incident rate for all MIs. Physical activity (PA) is an important health behavior to prevent a recurrent MI. Fatigue, sleepiness, anxiety, and depression are all barriers to PA. The purpose of this pilot study was to examine how fatigue tolerance, sleep, depression, and anxiety influenced PA in those attending cardiac rehabilitation (CR) after an MI or coronary artery bypass surgery. Using a repeated measure design, we interviewed a pilot sample of 8 adults who were beginning CR. Each participant completed a demographic and health status form. A 100mm visual analog scale was used to determine fatigue tolerance. Sleep was measured using the Epworth Sleepiness Scale, the Patient Health Questionnaire-9 measured depression, and anxiety was measured using the Generalized Anxiety Disorder-7. Participants wore a Garmin activity tracker for one week and step data (PA) were calculated on full days of activity. All data were analyzed using Statistical Package for Social Sciences 25. Most of the participants (N = 8) were White (88%), women (62.5%), and had a mean age of 70.5 (SD = 10.5). All had high cholesterol, 88% high blood pressure, and 38% had a history of smoking. The mean depression score was 7 (SD = 4.3; range 1-15) indicating mild depression. Sleep (M = 7.1; SD = 6) and anxiety (M = 4.88; SD = 5) were in normal ranges. Average number of daily steps was 6000 (SD = 2517; range = 2863-9526). The average fatigue that they could tolerate (M = 59; SD = 26.7) and the average fatigue that slowed them down (M = 49.6; SD = 24.7) were lower than their perceived normal fatigue level for people similar to them (M = 70.4; SD = 24). Average daily steps were negatively associated with fatigue level that slows them down (r = -.78) but none of the other fatigue tolerability measures correlated with PA.