Miracle-dz/UniFAR-FTUs huggingface dataset:
Importance of Wild Crucifers for Diamondback Moth, Plutella Xylostella L. (Lepidoptera: Plutellidae) and Its Parasitoids in Kenya

An investigation of the diversity and distribution of wild crucifer species and their importance for cultivated crucifers was conducted during 2005 and 2006 in the highland and mid-altitude semi-arid areas of Kenya. Thirteen species of wild crucifers in nine genera were recorded: Raphanus raphanistrum, Erucastrum arabicum, Sisymbrium officinale, Crambe kilimandscharica, Capsella bursa-pastoris, Rorippa nudiuscula, Ro. micrantha, Ro. microphylla, Lepidium bonariense, Coronopus didymus, Brassica rapa, B. juncea and Brassica species. Highland areas had significantly higher species diversity and species richness than mid-altitude semi-arid areas. Species richness, diversity and evenness varied with season and location. Raphanus raphanistrum was the dominant non-cultivated species in the highland, followed by E. arabicum, which was also present and dominant in the semi-arid study sites. Diamondback moth (DBM), Plutella xylostella L. , was recorded from ten wild crucifer species and R. raphanistrum and E. arabicum were the preferred host plant species. DBM numbers on wild crucifers were lower than on cabbage and kale in adjacent fields. Overall, five larval, one larvalpupal and one pupal parasitoid of DBM were recorded: Diadegma semiclausum, D. mollipla, Itoplectis sp. (highland only), Cotesia plutellae and Apanteles sp. (both semi-arid areas only), Oomyzus sokolowskii and Brachymeria species. Diadegma semiclausum was the most dominant species on all crucifers. Spatial niche separation was observed in Athi River where Apanteles and Brachymeria were collected on E. arabicum only. Higher numbers of D. mollipla were recovered from wild crucifers than cabbage and kale. We conclude that wild crucifers act as alternative hosts for DBM and provide refugia for parasitoids when the crop is absent and may help in recolonisation of cultivated crops after local extinction of parasitoids through pesticide application.
Investigating Listeners’ Responses to Divergent Recommendations

Recommender systems offer great opportunity not only for users to discover new content, but also for the providers of that content to find new audience, followers, and fans. Users often come to a recommender system with certain expectations about what it will recommend to them, and a recommender system that is optimized for creating opportunities for content creators may provide recommendations that are very different from what a user is expecting. We hypothesize that some users’ expectations have a much wider range of acceptability than others, and users with more ”receptivity” to subversion of their expectations are likely to accept such divergence in the recommended content. Understanding users’ responses to such recommendations is vital to platforms that need to serve multiple stakeholders. In this work we investigate logged behavioral responses of users of an audio streaming platform to recommendations that deviate from their expectation, or “divergent” recommendations. We present three classes of listener response to divergent recommendations that can be identified in interaction logs with the aim of predicting which users can be targeted for future divergent recommendations. We derive a number of user characteristics based on user’s music consumption which we think are predictive of user’s receptivity, train models to predict receptivity of these users, and run a live A/B test to validate our approach by correlating with engagement.
A Study of Feeding in Some Inshore Reef Fish of the Natal Coast, South Africa

A detailed quantitative investigation of the feeding habits of seven important Natal inshore reef fish (Epinephelus andersoni Boulenger, 1903, Coracinus mulfifasciafus (Pellegrin, 1914), Pomadasys olivaceum Day, 1875, Diplodus sargus Linnaeus, 1758, Sarpa salpa (Linnaeus, 1766), Acanthurus triosfegus Linnaeus, 1758 and Neoscorpls lithophilus (Gilchrist & Thompson, 1908)) is described. Qualitative information on the feeding of 23 other species is also given, and when all species are considered the ratio of carnivores, omnivores and herbivores is 4:1:1.
Modeling and Ranking Flaky Tests at Apple

Test flakiness-inability to reliably repeat a test’s Pass/Fail out come-continues to be a significant problem in Industry, adversely impacting continuous integration and test pipelines. Completely eliminating flaky tests is not a realistic option as a significant fraction of system tests (typically non-hermetic) for services-based implementations exhibit some level of flakiness. In this paper, we view the flakiness of a test as a rankable value, which we quantify, track and assign a confidence. We develop two ways to model flakiness, capturing the randomness of test results via entropy, and the temporal variation via flipRate, and aggregating these over time. We have implemented our flakiness scoring service and discuss how its adoption has impacted test suites of two large services at Apple. We show how flakiness is distributed across the tests in these services, including typical score ranges and outliers. The flakiness scores are used to monitor and detect changes in flakiness trends. Evaluation results demonstrate near perfect accuracy in ranking, identification and alignment with human interpretation. The scores were used to identify 2 causes of flakiness in the dataset evaluated, which have been confirmed, and where fixes have been implemented or are underway. Our models reduced flakiness by 44% with less than 1% loss in fault detection.
Microscope: mobile service traffic decomposition for network slicing as a service

The growing diversification of mobile services imposes requirements on network performance that are ever more stringent and heterogeneous. Network slicing aligns mobile network operation to this context, by enabling operators to isolate and customize network resources on a per-service basis. A key input for provisioning resources to slices is real-time information about the traffic demands generated by individual services. Acquiring such knowledge is however challenging, as legacy approaches based on in-depth inspection of traffic streams have high computational costs, which inflate with the widening adoption of encryption over data and control traffic. In this paper, we present a new approach to service-level demand estimation for slicing, which hinges on decomposition, i.e., the inference of per-service demands from traffic aggregates. By operating on total traffic volumes only, our approach overcomes the complexity and limitations of legacy traffic classification techniques, and provides a suitable input to recent 'Network Slice as a Service' (NSaaS) models. We implement decomposition through Microscope, a novel framework that uses deep learning to infer individual service demands from complex spatiotemporal features hidden in traffic aggregates. Microscope (i) transforms traffic data collected in irregular radio access deployments in a format suitable for convolutional learning, and (ii) can accommodate a variety of neural network architectures, including original 3D Deformable Convolutional Neural Networks (3D-DefCNNs) that we explicitly design for decomposition. Experiments with measurement data collected in an operational network demonstrate that Microscope accurately estimates per-service traffic demands with relative errors below 1.2%. Further, tests in practical NSaaS management use cases show that resource allocations informed by decomposition yield affordable costs for the mobile network operator.
Designing the Interaction of Highly Automated Vehicles with Cyclists in Urban Longitudinal Traffic: Relevant Use Cases and Methodical Considerations

In future urban traffic, highly automated vehicles (HAVs) will have to successfully interact with vulnerable road users, such as pedestrians and cyclists. While the interaction of HAVs with crossing pedestrians is already well studied, HAV interaction concepts for the encounters with cyclists are yet to be explored. We present a project that focuses on the user-centered design of HAV driving maneuvers for interactions with cyclists travelling upfront and in the same direction in urban longitudinal traffic. This work introduces the use cases and the methodical approach to explore current cyclist-vehicle interactions in a real life setting. With this approach, we aim to derive implications for the design of future HAV interaction behavior.
Analysis of Genetic Diversity on Beer Barley Varieties in China by SSR

The genetic relationships among 38 beer barley from China were investigated by SSR.The results showed that choosing 2 pairs separately in the long as well as short arms on the 7 pairs of chromosome in barley,in all,we got 28 pairs of SSR primer.26 pairs of SSR primer were detected to have polymorphism and 187 loci were measured totally.Therein,172 loci have polymorphism which occupies 91.9%. Each primer can augment 1-22 loci with 6.6 loci in the average.The polymorphism information content among the 26 pairs got the highest PIC 0.995 and the lowest 0.375,with the average 0.713 among the 26 pairs.Cluster analysis showed that 38 beer barley could be classified into 2 groups at the level of GD 0.6,which were respectively classified into 4 subgroups again.The GD varied from 0.01124 to 0.74510. Most beer barley had showed certain regular distribution in every subgroup.The results indicated that the genetic basis of them was rather narrow.
Enriching Programming Student Feedback with Audio Comments

Introductory programming is challenging for many students, requiring them to engage with a deep approach to learning concepts in order to succeed. These challenges compound for online students who do not have direct face-to-face interactions with teaching staff. With the growing demand for online education, we need to examine approaches that assist in building supportive learning environments for these students. A growing body of work from other education disciplines indicates that audio feedback provides an opportunity for developing stronger relationships with students. Further studies recommend an integrated implementation of audio recording into the virtual learning environment. To evaluate audio feedback for use in programming education, we developed an integrated, cross-browser audio feedback feature into the open-source Doubt-fire learning management system. Doubtfire is used to support and scale a task-oriented teaching and learning system built upon the principles of constructive alignment and has been shown to help students engage with programming concepts in campus-only units. Our findings from experimental and observational activities indicate that programming tutors can use a blended approach of audio and text feedback via the learning management system to better support student learning. The blended approach provides more nuanced feedback, conveying personality and feelings of connectedness to students, while retaining the benefits of specificity for code-specific issues.
LMAC: Efficient Carrier-Sense Multiple Access for LoRa

Current LoRa networks including those following the LoRaWAN specification use the primitive ALOHA mechanism for media access control due to LoRa’s lack of carrier sense capability. From our extensive measurements, the channel activity detection feature that was recently introduced to LoRa for energy-efficiently detecting preamble chirps can also detect payload chirps reliably. This sheds light on an efficient carrier-sense multiple access protocol that we refer to as LMAC for LoRa networks. This article presents the designs of three advancing versions of LMAC that respectively implement carrier-sense multiple access, and balance the communication loads among the channels defined by frequencies and spreading factors based on the end nodes’ local information and then additionally the gateway’s global information. Experiments on a 50-node lab testbed and a 16-node university deployment show that, compared with ALOHA, LMAC brings up to 2.2× goodput improvement and 2.4× reduction of radio energy per successfully delivered frame. Thus, should LoRaWAN’s ALOHA be replaced with LMAC, network performance boosts can be realized.
Effects of Exogenous Enzymes, Lactobacillus acidophilus or their Combination on Feed Intake, Digestibility and Performance of Rabbits Fed Sugarcane Bagasse

The aim of this study was to evaluate the effect of Lactobacillus acidophilus (LAC), exogenous enzymes ZAD® or their combination on feed intake, nutrient digestibility and performance of rabbits fed increasing levels of sugarcane bagasse (SCB). Five rations were allotted randomly to five groups of New Zealand white (NZW) rabbits (838±42.4g average BW at 5 weeks of age. Rabbits were fed: (i) a control diet made of 100% berseem hay and 0% SCB, (ii) 50% berseem hay and 50% untreated SCB (USCB), (iii) 50% berseem hay and 50% SCB treated with Lactobacillus acidophilus (LAC), (iv) 50% berseem hay and 50% SCB treated with ZAD® (ZAD), and (v) 50% berseem hay and 50% SCB treated with LAC+ZAD® (LZ). Treatment of SCB with Lactobacillus acidophilus, ZAD® and LAC+ ZAD® led to higher CP content and lower contents of ADF, NDF and DM. Total DM intake was not affected by treatments. Digestibility coefficient of CP for LAC and LZ were higher (P<0.05) compared to the other groups. The BW for LAC and LZ rabbits was higher (P<0.05) than for the other groups, while the BW for LAC rabbit was the highest (P<0.05) and for USCB was the lowest. It can be concluded that treating sugarcane bagasse with Lactobacillus acidophilus, exogenous enzymes of ZAD® or their combination improved feeding values; however, the treatment with Lactobacillus acidophilus was found to be the best.
Investigating the Impact of Audio States & Transitions for Track Sequencing in Music Streaming Sessions

Music streaming is inherently sequential in nature, with track sequence information playing a key role in user satisfaction with recommended music. In this work, we investigate the role audio characteristics of music content play in understanding music streaming sessions. Focusing on 18 audio attributes (e.g. dancability, acousticness, energy), we formulate audio transitioning in a session as a multiple changepoint detection problem, and extract latent states of different audio attributes within each session. Based on insights from large scale music streaming data from a popular music streaming platform, we investigate questions around the extent to which audio characteristics fluctuate within streaming sessions, the heterogeneity across different audio attributes and their impact on user satisfaction. Furthermore, we demonstrate the promise of such audio-based characterizing of sessions in better sequencing tracks in a session, and highlight the potential gains in user satisfaction on offer. We discuss implications on the design of track sequencing models, and identify important prediction tasks to further research on the topic.
Lack of Adoption of Units of Measurement Libraries: Survey and Anecdotes

Units of measurement (UoM) libraries are mostly used to appropriately encode unit variables and convert between them in a typesafe manner. Approximately 3700 functioning unit measurement libraries exist on the web, indicating that the wheel is being reinvented time and time again. Previous research has postulated that too much diversity, lack of code sharing and duplicated efforts are discouraging adoption, yet more remains to be known. Three developers and a scientist were interviewed and 91 practitioners of varying experiences from online forums were surveyed to explain their dissatisfaction with UoM libraries and possible reasons behind the lack of adoption. Our findings range from insufficient awareness of these UoM’s, to development processes that exclude unit information through to specific performance concerns. We conclude with recommendations to UoM library creators stemming from these points that could help alleviate the problem and lead to an increased adoption rate of methodologies that support unit annotation and checking.
International consensus on pressure injury preventative interventions by risk level for critically ill patients: A modified Delphi study

The aim of this modified Delphi study was to determine a minimum pressure injury preventative intervention set for implementation relative to critically ill patients' risk level. Preventative interventions were identified via systematic review, risk levels categorised by an intensive‐care‐specific risk‐assessment‐scale (COMHON Index), and panel members (n = 67) identified through an international critical care nursing body. Round 1: panel members were asked to rate implementation of 12 interventions according to risk level (low, moderate, high). Round 2: interventions were rated for use at the risk level which received greatest round 1 support. Round 3: interventions not yet achieving consensus were again rated, and discarded where consensus was not reached. Consensus indicated all patients should receive: risk assessment within 2‐hours of admission; 8‐hourly risk reassessment; and use of disposable incontinence pads. Additionally, moderate‐ and high‐risk patients should receive: a reactive mattress support surface and a heel off‐loading device. High‐risk patients should also receive: nutritional supplements if eating orally; preventative dressings (sacral, heel, trochanteric); an active mattress support surface; and a pressure‐redistributing cushion for sitting. Repositioning is required at least 4‐hourly for low‐risk, and 2‐hourly for moderate‐ and high‐risk patients. Rigorous application of the intervention set has the potential to decrease pressure injuries in intensive care.
Large Dimensional Analysis and Improvement of Multi Task Learning

Multi Task Learning (MTL) efficiently leverages useful information contained in multiple related tasks to help improve the generalization performance of all tasks. This article conducts a large dimensional analysis of a simple but, as we shall see, extremely powerful when carefully tuned, Least Square Support Vector Machine (LSSVM) version of MTL, in the regime where the dimension $p$ of the data and their number $n$ grow large at the same rate. Under mild assumptions on the input data, the theoretical analysis of the MTL-LSSVM algorithm first reveals the "sufficient statistics" exploited by the algorithm and their interaction at work. These results demonstrate, as a striking consequence, that the standard approach to MTL-LSSVM is largely suboptimal, can lead to severe effects of negative transfer but that these impairments are easily corrected. These corrections are turned into an improved MTL-LSSVM algorithm which can only benefit from additional data, and the theoretical performance of which is also analyzed. As evidenced and theoretically sustained in numerous recent works, these large dimensional results are robust to broad ranges of data distributions, which our present experiments corroborate. Specifically, the article reports a systematically close behavior between theoretical and empirical performances on popular datasets, which is strongly suggestive of the applicability of the proposed carefully tuned MTL-LSSVM method to real data. This fine-tuning is fully based on the theoretical analysis and does not in particular require any cross validation procedure. Besides, the reported performances on real datasets almost systematically outperform much more elaborate and less intuitive state-of-the-art multi-task and transfer learning methods.
INTRODUCTION During vertebrate embryogenesis neural crest cells delaminate from the dorsal neural tube, migrate throughout the body and differentiate into a remarkably diverse array of cell types (Le

During vertebrate embryogenesis neural crest cells delaminate from the dorsal neural tube, migrate throughout the body and differentiate into a remarkably diverse array of cell types (Le Douarin and Kalcheim, 1999; Smith et al., 1994). These neural crest fates can be broadly categorized as ectomesenchymal and nonectomesenchymal. The ectomesenchymal neural crest fates include cranial cartilage and fin mesenchyme (in fish) whereas the nonectomesenchymal fates include neurons and glia of the peripheral nervous system and pigment cells. Defects in neural crest development are a significant cause of human disease and the resulting syndromes are termed neurocristopathies (Le Douarin and Kalcheim, 1999). One such neurocristopathy is Waardenburg’s Syndrome, in which individuals have dominant pigmentation defects. Waardenburg’s Syndrome types IIa and IV are associated with haploinsufficiency for the transcription factor genes MITF and SOX10, respectively (Pingault et al., 1998; Tachibana et al., 1994; Tassabehji et al., 1994). Zebrafish or mice homozygous for mutations in the sox10 transcription factor gene [previously called colourless(cls) in zebrafish] have severe defects in all the nonectomesenchymal neural crest cell fates (Dutton et al., 2001; Herbarth et al., 1998; Kelsh and Eisen, 2000; Southard-Smith et al., 1998). In cls/sox10–/– zebrafish many neural crest cells undergo apotoptic cell death near the neural tube. They do so after failing to become specified or migrate (Dutton et al., 2001). Apoptotic death of cells on the neural crest migration pathways has also been reported in Sox10–/– mouse embryos (Kapur, 1999). In cls/sox10–/– zebrafish and in Sox10–/– mouse embryos some of the nonectomesenchymal neural crest cell fates such as melanocytes (also called melanophores in zebrafish) and peripheral glia are essentially absent whereas others such as the dorsal root ganglia sensory neurons do form but with fewer and disorganized cells (Britsch et al., 2001; Kelsh and Eisen, 2000; Sonnenberg-Riethmacher et al., 2001; Southard-Smith et al., 1998). In mammalian systems it has been shown that in the case of the peripheral glia a major requirement of Sox10is to directly regulate expression of terminal differentiation genes such as P0 and Cx32 (Gjb1 – Mouse Genome Informatics) (Bondurand et al., 2001; Peirano et al., 2000). Sox10also regulates expression of the neuregulin receptor gene, Erbb3 (Britsch et al., 2001). Signaling through Erbb3promotes acquisition of the glial fate 2809 Development 130, 2809-2818 © 2003 The Company of Biologists Ltd doi:10.1242/dev.00461
High School Size and Achievement of English Language Learner Boys and Girls: A Multiyear Analysis

In this investigation, the academic achievement of English Language Learner boys and girls on the Texas Assessment of Knowledge and Skills Exit-Level Reading and Mathematics tests by school size was examined. Previously obtained archival data for two school years from the Texas Education Agency were utilized. School size groupings were formed using the [47] categories for student enrollment. Inferential analyses revealed the presence of statistically significant differences for boys and for girls across both school years and both TAKS tests as a function of high school size. In all cases, reading and mathematics achievement was higher for English Language Learner boys and girls in Medium-size to Large-size (1,060-2,099 students) high schools than in Small-size (105-219 students) through Moderate-size (465-1,059) high schools. Implications for policy and practice, as well as recommendations for research, are provided.