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opencc-by-4.0Jun 2021View details →

Dataset: What are the characteristics of highly-used packages? A case study on the npm ecosystem

With the popularity of software ecosystems, the number of open source components (a.k.a. “packages”) has been growing rapidly. Identifying high-quality and well-maintained packages from a large pool of packages to depend on is a basic and important problem, as it is beneficial for various applications, such as package recommendation, package search, etc. However, there is no systematic and comprehensive work so far that focuses on addressing this problem except in online discussions or in informal literature and interviews. To fill this gap, in this paper, we conduct a mixed qualitative and quantitative analysis to understand how developers identify and select relevant open source packages. In particular, we start by surveying 118 JavaScript developers from the npm ecosystem to qualitatively understand the factors that make a package to be highly-used within the ecosystem. The survey results show that JavaScript developers believe that highly-used packages are well-documented, receive a high number of stars on GitHub, have a large number of downloads, and do not suffer from vulnerabilities. Then, we conduct an experiment to quantitatively validate the developers' perception of the factors that make a highly-used package. In this analysis, we collect and mine historical data from 2,427 packages divided into highly-used and low-used packages. For each package in the dataset, we collect quantitative data to present the factors studied in the developers' survey. Next, we use regression analysis to quantitatively explain which of the studied factors are the most important. Our regression analysis support developers' believe about highly-used packages. In particular, the results show that highly-used packages tend to be impacted by the number of downloads, stars, and how larger is readme file of the package.

opencc-by-4.0Jun 2022View details →

Hyperglycemia and steroid use increase the risk of rhino-orbito-cerebral mucormycosis regardless of COVID-19 hospitalization: Case-control study, India

Abstract BACKGROUND In the context of the ongoing COVID-19 pandemic increased incidence of ROCM was noted in India, among those infected with COVID. We determined risk factors for rhino-orbito-cerebral mucormycosis (ROCM) post Coronavirus disease 2019 (COVID-19) among those never and ever hospitalized for COVID-19 separately through a multi-centric, hospital-based, unmatched case-control study across India. METHODS We defined cases and controls as those with and without post-COVID ROCM, respectively. We compared their socio-demographics, comorbidities, steroid use, glycaemic status, and practices. We calculated crude and adjusted odds ratio (AOR) with 95% confidence intervals (CI) through logistic regression. The covariates with p-value for crude OR of less 0·20 were considered for the regression model. RESULTS Among hospitalised, we recruited 267 cases and 256 controls and 116 cases and 231 controls among never hospitalised. Risk factors (AOR; 95% CI) for post-COVID ROCM among the hospitalised were age 45-59 years (2·1; 1·4 to 3·1), having diabetes mellitus (4·9; 3·4 to 7·1), elevated plasma glucose (6·4; 2·4 to 17·2), steroid use (3·2; 2 to 5·2) and frequent nasal washing (4·8; 1·4 to 17). Among those never hospitalised, age ≥ 60 years (6·6; 3·3 to 13·3), having diabetes mellitus (6·7; 3·8 to 11·6), elevated plasma glucose (13·7; 2·2 to 84), steroid use (9·8; 5·8 to 16·6), and cloth facemask use (2·6; 1·5 to 4·5) were associated with increased risk of post-COVID ROCM. CONCLUSIONS Hyperglycemia irrespective of having diabetes mellitus and steroid use was associated with increased risk of ROCM independent of COVID-19 hospitalisation. Rational steroid usage and glucose monitoring may reduce the risk of post-COVID.

opencc-by-4.0Sep 2021View details →

Classification of hierarchical text using geometric deep learning: the case of clinical trials corpus

We consider the hierarchical representation of documents as graphs and use geometric deep learning to classify them into different categories. While graph neural networks can efficiently handle the variable structure of hierarchical documents using the permutation invariant message passing operations, we show that we can gain extra performance improvements using our proposed selective graph pooling operation that arises from the fact that some parts of the hierarchy are invariable across different documents. We applied our model to classify clinical trial (CT) protocols into completed and terminated categories. We use bag-of-words based as well as pre-trained transformer-based embeddings to featurize the graph nodes, achieving f1-scores $\simeq 0.85$ on a publicly available large scale CT registry of around 360K protocols. We further demonstrate how the selective pooling can add insights into the CT termination status prediction.

dryad40/100

Congruence among multiple indices of habitat preference for species facing human-induced rapid environmental change: A case study using the Brewer's sparrow

Accurate evaluations of habitat preference are key to understanding optimal conditions for wildlife survival and reproduction. Habitat selection, however, usually is evaluated using a single index of preference, and congruence among multiple, relevant indices of preference is examined rarely. We assessed the concordance between patterns of habitat preference using three different indices of breeding site preference in a migratory songbird. Specifically, we compared the chronology of territorial establishment, pair formation, and reproductive initiation of the Brewer's sparrow (Spizella breweri) along a gradient of surface disturbance associated with natural gas development in Wyoming, USA during 2019. We expected all three indices to demonstrate a preference for breeding sites with less surface disturbance, where reproductive success typically is higher. By contrast, all indices suggested suboptimal preference with respect to surface disturbance, with some discrepancy among them. The chronology of settlement and pairing did not vary across the disturbance gradient, whereas nest initiation tended to occur earlier at sites with more disturbance. If the pattern of suboptimal selection of breeding sites that we identified is generalizable across other populations of migratory birds affected by energy development, the resultant lower fitness in those areas may exacerbate population declines. Our results suggest that traditional, single-index approaches to the study of habitat selection, if chosen carefully, may provide adequate inference on habitat preferences. Different metrics, however, can lead to at least subtle differences in patterns of habitat selection. The simultaneous examination of multiple indices of preference across a diversity of systems would help clarify the contexts under which preference metrics can become decoupled.

opencc-zeroSep 2022View details →

opencc-by-4.0Aug 2022View details →

Text-fig. 4. Graphical visualization of Phytogeographic Reference Regions Assessment (PRRA) of nearest living relative genera of fossil-taxa from late Early Miocene Wiesa assemblage in eastern Germany. Analysis yields only NLRs which have modern distribution area (partly) in E and SE Asia. For relationships of fossil-taxa to nearest living relatives or ecological equivalents, see Tab. 6; taxa used for analysis marked with asterisks. Three geographic resolutions conducted: a – grid with 1.5° latitude/longitude resolution, b – grid with 2°, c – grid with 3°; similarity column indicates cooccurrences of genera of nearest living relatives in single grid box. Maximum value in our analysis: grid box marked with arrow in map a, located in western Yunnan Province, P. R. China and southern Kachin Province, NE Myanmar (east of Myitkyina city), area with 97.371 7–98.874 2° longitude and 24.586 7–25.837 5° latitude, yields 23 co-occurring species of 13 genera (Tab. 7). in Assessment Of Phytogeographic Reference Regions For Cenozoic Vegetation: A Case Study On The Miocene Flora Of Wiesa (Germany)

Text-fig. 4. Graphical visualization of Phytogeographic Reference Regions Assessment (PRRA) of nearest living relative genera of fossil-taxa from late Early Miocene Wiesa assemblage in eastern Germany. Analysis yields only NLRs which have modern distribution area (partly) in E and SE Asia. For relationships of fossil-taxa to nearest living relatives or ecological equivalents, see Tab. 6; taxa used for analysis marked with asterisks. Three geographic resolutions conducted: a – grid with 1.5° latitude/longitude resolution, b – grid with 2°, c – grid with 3°; similarity column indicates cooccurrences of genera of nearest living relatives in single grid box. Maximum value in our analysis: grid box marked with arrow in map a, located in western Yunnan Province, P. R. China and southern Kachin Province, NE Myanmar (east of Myitkyina city), area with 97.371 7–98.874 2° longitude and 24.586 7–25.837 5° latitude, yields 23 co-occurring species of 13 genera (Tab. 7).

opencc-by-4.0Apr 2024View details →

DATA: Chatbots in Airport Customer Service – Exploring Use Cases and Technology Acceptance

This dataset (n=191) investigates use cases and technology acceptance of chatbots in airport customer service.

Fig. 5 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 5: Distribution and abundance maps of eggs during May (A, B) and July 2010 (C-E), in the NE Aegean Sea. The major patches are indicated by different colours, while the size of the circles is scaled by the maximum abundance per species and period (Table 2). The number of each patch indicates the ranking according to the abundance of individuals in each patch. The small black cross symbols show the centres of gravity (CG) of each major patch (i.e. those patches having more than 10% of the overall abundance; Table 3). The large cross indicates the CG of the population. The length of the cross axes indicate the isotropy of the egg distribution. The 200m isobaths are also shown (dark contour line).

Fig. 4 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 4: Box-and-whisker plots for temperature (oC; at 10 m depth), salinity (at 10 m depth), log-transformed integrated fluorescence (μg l-1) and log-transformed mesozooplankton biomass (mg m-2) between three groups of sampling stations: L – Lemnos plateau, O – offshore pelagic area north of Lemnos island, and T- Thracian Sea shelf. Boxes indicate median and interquartile ranges, whiskers delineate full ranges. F-values are provided for comparisons of the parameters between the three groups (L, O, T) and within each season. For comparisons that did not meet the assumptions of the analysis of variance, the Kruskal-Wallis statistic H is provided. Asterisks indicate significant differences: *p <0.05, **p <0.01, ***p <0.001. Post-hoc multiple comparisons were performed with a Student-Newman-Keul's test, where statistically significant differences among groups are indicated by letters a, b, c on the left side of each box. Groups with the same letter do not differ significantly.

Fig. 3 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 3: Contour maps of the vertical distribution of temperature (oC; left column), salinity (middle column) and fluorescence (μg Chlα l-1; right column) during May 2010 along transect A (A-C) and transect B (D-F), and during July 2010 along transects A (H-J) and B (K-M). Y-axis: depth of the water column; X-axis: distance (nmi) from the northern sampling station (0 nmi) to the southern station. The position (distance, nmi) of the sampling stations along the transects are shown in white, dashed lines on top of the temperature contour maps.

Fig. 2 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 2: Temperature (oC, 10 m depth; A, E), salinity (10 m; B, F), integrated fluorescence (μg Chl-a l-1, 0-100 m; C, G) and mesozooplankton biomass (mg m-2; D, H) during May (A-D) and July 2010 (E-H) in the study area.

Fig. 1 in Using spatial indicators to investigate fish spawning strategies from ichthyoplankton surveys: A case study on co-occurring pelagic species from the North-East Aegean Sea Abstract

Fig. 1: Ichthyoplankton (shown as open red circles) and CTD sampling stations (shown as filled red circles) during May and July 2010. The isobaths of 100 and 200 m are shown (light and dark blue lines, respectively). Black arrows indicate the main circulation pattern in the area: LIS - Lemnos-Imvros stream, SG - Samothraki gyre (Somarakis et al., 2002). The sampling stations of transects A and B (grey lines) show the vertical structure of the water column in Figure 3.

opencc-by-4.0Jul 2024View details →

5G-IANA: UC4 Dataset Mobile users data rate participating in the use case

Location of the mobile user and its nearby place data including their type such as restaurant, café, market, banks and gas station

Figure 4 in Fishers' perceptions of river resources: case study of French Guiana native populations using contextual cognitive mapping

Figure 4. – Cognitive maps focused on a minimum common overview (gray concepts and edges (incoming arrows)) and village-specific overviews (white concepts and blue (5 Amerindian villages) or brown (2 Aluku villages) edges) of threats to the fish resource and environment.

FIGURE 16 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)

FIGURE 16. Detailed images of the EFS of both the SMA 0084 "Rich" samples. A, EFS of SMA 0084 "Rich" tibia, in which a cycle of faster growth is included (indicated by arrow). B, EFS of SMA 0084 "Rich" fibula, which also shows a cycle of faster growth (indicated by arrow). Images taken under plane-polarized light.

FIGURE 13 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)

FIGURE 13. Images of all forelimb samples taken from SMA 0011 "Max". A, humerus (r). B, humerus (l). C, ulna (l). D, radius (l). For all samples, the bone tissue types are indicated to the left, and the number and patterns of the visible growth cycles are indicated to the right. Abbreviations; D: Bone tissue type D, E: Bone tissue type E, F: Bone tissue type F, MC: Medullary cavity, RA: Remodeled area.

FIGURE 2 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)

FIGURE 2. Detailed quarry map of the Howe Scott Quarry with finds from excavation seasons 1995-2003. The color coding reflects the hypothesis of skeletal unity based on field observations (Ayer, 2000). Sauropods are indicated in red in the legend. The arrows indicate the sampled bones used in this study. The quarry map was made by E. Premru, and provided by the Sauriermuseum Aathal, Aathal, Switzerland. Note that SMA M16/12-3 is not marked on the map due to a coordinate inaccuracy, which makes it impossible to correctly locate bone SMA M16/12-3 on the quarry map.

FIGURE 1 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)

FIGURE 1. Detailed quarry map of the Howe-Stephens Quarry with finds from excavation seasons 1992-2001. The color coding reflects the hypothesis of skeletal unity based on field observations (Ayer, 2000). Sauropods are indicated in red text in the legend. Note that the 2002 season, which was the last season for the Howe-Stephens Quarry, only uncovered another silicified tree trunk, which was found below the partial skeletons of SMA 0002 "E.T." and SMA no # "Brösmeli". The arrows indicate the sampled bones used in this study. This quarry map was made by E. Premru, and provided by the Sauriermuseum Aathal, Aathal, Switzerland.

FIGURE 15 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)

FIGURE 15. Images of both samples taken from SMA 0084 "Rich". A, tibia (l). B, fibula (l). For all samples, the bone tissue types are indicated to the left, and the number and patterns of the visible growth cycles are indicated to the right. Abbreviations; EFS: External fundamental system, MC: Medullary cavity, RA: Remodeled area.

FIGURE 3 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)

FIGURE 3. The innermost cortex of fibula SMA 0084 "Rich" with the three visible generations of secondary osteons. The numbers indicate the three overlapping secondary osteons. Image taken under plane-polarized light.

FIGURE 12 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)

FIGURE 12. Several histological structures observed in the anterior section of the femur of SMA 0014 "Jacques". A, Large circular structure, which possesses clear circumferentially orientated vascular canals. B, Close-up of the circular structure and the vascular canals. C, D, F, Cycles which show unorganized bone tissue, and varying vascular canal orientations. E, Close-up of unorganized bone tissue cycle. Images taken under plane-polarized light.