Miracle-dz/UniFAR-FTUs huggingface dataset:
Diversity, biology, and management of the pear psyllids: a global look

The pear psyllids (Cacopsylla Ossiannilsson; Hemiptera: Psylloidea: Psyllidae) are a taxonomically difficult group of at least 24 species native to the Palaearctic region. One or more species occur in most pear-growing regions, in some cases as invasive introductions. Existing reviews of this group are primarily of taxonomic focus with limited overviews of biology. The earliest biological studies of the pear psyllids centered on a core group of a few western European species. In part, this focus arose because diversity of the pear psyllids was poorly understood. As taxonomic understanding has advanced over the last 3 decades, research has expanded taxonomically. Increasing difficulties in controlling the pear psyllids additionally has contributed to growth in research. Here, we review a now-extensive literature on diversity, biology, and management of the pear psyllids. Three broad observations emerged from this synthesis. First, large gaps in biological understanding of the pear psyllids persist for several geographic faunas, most notably for psyllids of the Eastern Palaearctic region. Second, taxonomic diversity is accompanied by biological diversity. Despite the commonality in host use among the pear psyllids, with each species being limited to development on Pyrus, striking differences exist among species in life cycles, wintering, and other biological traits. Third, many of the tools being used to manage pear psyllids today are in existence because of the long history of basic research which has targeted these pests. These tools include new insecticides of higher selectivity, various cultural and horticultural tactics, and practices that conserve natural enemies in orchards.
Quantification of sporozoite expelling by Anopheles mosquitoes infected with laboratory and naturally circulating P. falciparum gametocytes

It is currently unknown whether all Plasmodium falciparum infected mosquitoes are equally infectious. We assessed sporogonic development using cultured gametocytes in the Netherlands and naturally circulating strains in Burkina Faso. We quantified the number of sporozoites expelled into artificial skin in relation to intact oocysts, ruptured oocysts, and residual salivary gland sporozoites. Sporozoites were quantified by highly sensitive qPCR; intact and ruptured oocysts by fluorescence microscopy following antibody staining of circumsporozoite protein. In laboratory conditions, higher total sporozoite burden in mosquitoes was associated with a shorter duration of sporogony (p<0.001). Overall, 53% (116/216) of P. falciparum infected An. stephensi mosquitoes expelled sporozoites into artificial skin. The medians of expelled and residual salivary gland sporozoites were 136 (IQR: 34-501) and 23,947 (IQR: 9127-78,380), respectively. There was a strong positive correlation between ruptured oocyst number and salivary gland sporozoite load (ρ=0.8; p<0.0001) and a weaker positive correlation between salivary gland sporozoite load and the number of sporozoites expelled (ρ=0.35; p=0.0002). In Burkina Faso, An. coluzzii mosquitoes were infected by natural gametocyte carriers. Among mosquitoes that were salivary gland sporozoite positive, 89% (33/37) expelled sporozoites with a median of 1035 expelled sporozoites (IQR: 171-2969) and harbored a median of 45,100 residual salivary gland sporozoites (IQR: 20,310-164,900). Again, we observed a strong correlation between ruptured oocyst number and salivary gland sporozoite load (ρ=0.9; p<0.0001) and a positive correlation between salivary gland sporozoite load and the number of sporozoites expelled (ρ=0.7; p<0.0001). Mosquito salivary glands in Burkina Faso harbored 1-3 distinct parasite clones; several mosquitoes expelled multiple parasite clones during probing. Whilst sporozoite expelling was regularly observed from mosquitoes with low infection burdens, our findings indicate that mosquito infection burden is associated with the number of expelled sporozoites. Future work is required to determine the direct implications of these findings for transmission potential.
Making Sense of Neural Networks in the Light of Evolutionary Optimization

To what extent can evolution be considered as the sole first principle that explains all properties of nervous systems? This paper proposes an innovative, mathematically rigorous perspective on understanding nervous systems from an evolutionary perspective, leveraging methods of nonequilibrium statistical physics. This approach allows for modeling an exhaustive evolutionary optimization of nervous systems irrespective of any specific molecular and cellular mechanisms, approximate neuronal models or evolutionary history events. This novel method may shed light on key properties of biological neural networks and may also have potential relevance for understanding artificial neural networks.
The ubiquity of clonal interference in cancer and other range expansions

Evolution during range expansions shapes the fate of many biological systems including tumours, microbial communities, and invasive species. A fundamental process of interest is the selective sweep, in which an advantageous mutation evades clonal interference and spreads through the population to fixation. However, most theoretical investigations of selective sweeps have assumed constant population size or have ignored spatial structure. Here we use mathematical modelling and analysis to investigate selective sweep probabilities in populations that spread outwards as they evolve. In the case of constant radial expansion speed, we derive probability distributions for the arrival time and location of the first surviving mutant and hence find surprisingly simple approximate and exact expressions for selective sweep probabilities in one, two and three dimensions, which are independent of mutation rate. Namely, the selective sweep probability is approximately (1 cwt/cm)d, where cwt and cm are the wildtype and mutant radial expansion speeds, and d the spatial dimension. Using agent-based simulations, we show that our analytical results accurately predict selective sweep frequencies in the two-dimensional spatial Moran process. We further compare our results with those obtained for alternative growth models. Parameterizing our model for human tumours, we find that selective sweeps are predicted to be rare except during very early solid tumour growth, thus providing a general, pan-cancer explanation for findings from recent sequencing studies.
Pathogenic IgE-fated B cell memory retains functional plasticity

Long-lived immunoglobulin (Ig) E responses against innocuous environmental and dietary antigens (Ags) are maintained by an IgG1-dominant memory B cell (MBC) compartment primed for IL-4 responsiveness. In this work, we investigated the plasticity of the MBC compartment fated for IgE class switch recombination upon Ag re-exposure. Antibody-mediated IL-4R( blockade augmented the germinal center response and uncovered an IL-4/IL-13 dependency within the type 2 memory B cell (MBC2) skewed phenotype. In the absence of IL-4/IL-13 signaling during the recall response, a long-lived Ag-specific IgG2c MBC population emerged, shifting the MBC response away from a type 2 phenotype and towards type 1. The emergence of this IgG2c response was dependent on IFN-( signaling and arose from both unswitched and class-switched Ag-specific B cells in vivo. We further demonstrated that a type 1-polarizing adjuvant can augment the redirection of type 2-polarized class-switched MBCs, suggesting with the correct cues pathogenic MBCs can be functionally reprogrammed. One Sentence Summary B cell responses to allergens can be reprogrammed away from a pathogenic fate through IL-4/IL-13 signaling blockade.
The Kumaun and Garwhal Lesser Himalaya, India: Part 2. Thermal and deformation histories

An integrated petrologic, thermochronologic, and numerical modeling study constrains the thermal evolution of the Lesser Himalayan Sequence in the Kumaun and Garwhal regions of India. South of the Tons thrust, peak metamorphic temperatures do not exceed 330 °C. On the northern side, a transition toward higher temperatures adjacent to the Main Central thrust hanging wall is documented. In the immediate footwall of the Main Central thrust, peak temperatures average ~550 °C. An inverted thermal field gradient of ~30 °C/km beneath the Vaikrita thrust is calculated. An inverted thermal field gradient of ~20 °C/km is also documented beneath a klippe of the Main Central thrust hanging wall ~25 km south of the Vaikrita thrust, and a peak footwall temperature of 530 °C is recorded close to the shear zone at the base of the klippe. The mechanism for thermal metamorphism in the Lesser Himalayan Sequence is interpreted to be conduction of heat from the Main Central thrust fault and/or hanging wall to the footwall. A localized thermal field gradient is also associated with the Tons thrust. The ^(40)Ar/^(39)Ar thermochronology reveals that the exposed rock in the Kumaun and Garwhal Lesser Himalaya underwent cooling below the closure temperature (Tc) for white mica at different times in the late Tertiary. The proximal footwall of the Munsiari thrust experienced cooling below the white mica Tc at ca. 8.5 Ma. South of the Munsiari thrust, in the proximal footwalls of the Chaukori and Askot klippen, muscovites ages are ca. 11.5 Ma, ~3 Ma older than samples to the north. The age differences in samples from northern and southern exposures are interpreted to document cooling related to thermal relaxation following passage of the Main Central thrust hanging wall atop the Lesser Himalayan Sequence. Results of thermal modeling achieve good fits to the data when scenarios involve an early Miocene phase of overthrusting of a hot hanging wall over a downgoing footwall, followed by the initiation of a duplex within Lesser Himalayan Sequence rocks.
Iterates of meromorphic functions on escaping Fatou components

In this paper, we prove that the ratio of the modulus of the iterates of two points in an escaping Fatou component could be bounded even if the orbit of the component contains a sequence of annuli whose moduli tend to infinity, and this cannot happen when the maximal modulus of the meromorphic function is uniformly large enough. In this way we extend certain related results for entire functions to meromorphic functions with infinitely many poles.
Know When to Run: Recommendations in Crowdsourcing Contests

Crowdsourcing contests have emerged as an innovative way for firms to solve business problems by acquiring ideas from participants external to the firm. As the number of participants on crowdsourcing contest platforms has increased, so has the number of tasks that are open at any time. This has made it difficult for solvers to identify tasks in which to participate. We present a framework to recommend tasks to solvers who wish to participate in crowdsourcing contests. The existence of competition among solvers is an important and unique aspect of this environment, and our framework considers the competition a solver would face in each open task. As winning a task depends on performance, we identify a theory of performance and reinforce it with theories from learning, motivation, and tournaments. This augmented theory of performance guides us to variables specific to crowdsourcing contests that could impact a solver’s winning probability. We use these variables as input into various probability prediction models adapted to our context, and make recommendations based on the probability or the expected payoff of the solver winning an open task. We validate our framework using data from a real crowdsourcing platform. The recommender system is shown to have the potential of improving the success rates of solvers across all abilities. Recommendations have to be made for open tasks and we find that the relative rankings of tasks at similar stages of their time lines remain remarkably consistent when the tasks close. Further, we show that deploying such a system should benefit not only the solvers, but also the seekers and the platform itself.
CrashFormer: A Multimodal Architecture to Predict the Risk of Crash

Reducing traffic accidents is a crucial global public safety concern. Accident prediction is key to improving traffic safety, enabling proactive measures to be taken before a crash occurs, and informing safety policies, regulations, and targeted interventions. Despite numerous studies on accident prediction over the past decades, many have limitations in terms of generalizability, reproducibility, or feasibility for practical use due to input data or problem formulation. To address existing shortcomings, we propose Crash-Former, a multi-modal architecture that utilizes comprehensive (but relatively easy to obtain) inputs such as the history of accidents, weather information, map images, and demographic information. The model predicts the future risk of accidents on a reasonably acceptable cadence (i.e., every six hours) for a geographical location of 5.161 square kilometers. CrashFormer is composed of five components: a sequential encoder to utilize historical accidents and weather data, an image encoder to use map imagery data, a raw data encoder to utilize demographic information, a feature fusion module for aggregating the encoded features, and a classifier that accepts the aggregated data and makes predictions accordingly. Results from extensive real-world experiments in 10 major US cities show that CrashFormer outperforms state-of-the-art sequential and non-sequential models by 1.8% in F1-score on average when using "sparse" input data.
Information Technology and Administrative Efficiency in U . S . State Governments – A Stochastic Frontier Approach

This paper aims at exploring value creation from in formation technologies in governments. While the majority of studies in the information systems discipline have focused on discovering IT business value in for-profit organizations, the que stion of whether the performance effect of IT exists in the public sector has not been extensivel y studied so far in either the information systems or public administration literature. We examine whe ther IT improves administrative efficiency in U.S. state governments. Utilizing the IT budget dat a in state governments, the census data on state government expenditures, and a variety of inf rmation on public services states provide, we estimate technical cost inefficiency, an inverse pr oxy for administrative efficiency, with a stochastic frontier model. Our analyses provide evi d nce for a significantly negative relationship between IT intensity and cost inefficiency. Our res ults indicate that all others being equal, on average, a $1 increase in per capita IT budget can lead to $4.18 efficiency gains. This study contributes to the IS literature by expanding the s cope of IT value research to the public sector organizations and brings a new methodological appr oach to measure the performance impact of IT.
Technology Support and Post-Adoption IT Service Use: Evidence from the Cloud

Does a provider’s technology support strategy influence its buyers’ post-adoption IT service use? We study this question in the context of cloud infrastructure services. The provider offers two levels of support, basic and full. Under basic support, the provider handles simple service quality issues. Under full support, the provider also offers education, training, and personalized guidance through two-way interactions with buyers. Using unique data on public cloud infrastructure services use by 22,179 firms from March 2009 to August 2012 and fixed effects dynamic panel data models, we find that buyers who opt for full support use 34.38% more of the service as well as increase the fraction of servers they run in parallel by 3.56 percentage points relative to those who do not. Furthermore, buyers who opt to switch back to basic support from full support continue using 15.58% more of the service and have a proportion of servers running in parallel 4.36 percentage points higher compared to buyers who have never accessed full support. We also find that in the long-run these effects of support on volume and efficiency of usage do not disappear. These findings provide suggestive evidence of buyer learning as a result of provider support.
Evaluation of the effect of lunar cycle and monsoon on catch of yellowfin tuna

The sea around Andaman and Nicobar islands is one of the best tuna fishing ground and catches of yellowfin tuna forms a major constituent of Tuna longline fishery. The present study is an attempt to evaluate the effect of the lunar cycle and monsoon on the catch rate of yellowfin tuna based on exploratory tuna longline survey carried out by M.V. Blue Marlin, Fishery Survey of India, Port Blair. Present study provided information on the abundance of resources in time and space, environmental factors affecting its distribution and its significance in abundance of yellowfin tuna. The results of the present study indicated that there is a significant effect of the lunar cycle on the catch rate of yellowfin tuna occurring in the Andaman and Nicobar waters. The result showed that monsoon also significantly affects the catch rates of yellowfin tuna. Downward trend of year wise catch rate noticed during the study period warrant strict management measures on the tune longline fishery.
SIMD Dataflow Co-optimization for Efficient Neural Networks Inferences on CPUs

—We address the challenges associated with deploying neural networks on CPUs, with a particular focus on minimizing inference time while maintaining accuracy. Our novel approach is to use the dataflow (i.e., computation order) of a neural network to explore data reuse opportunities using heuristic-guided analysis and a code generation framework, which enables exploration of various Single Instruction, Multiple Data (SIMD) implementations to achieve optimized neural network execution. Our results demonstrate that the dataflow that keeps outputs in SIMD registers while also maximizing both input and weight reuse consistently yields the best performance for a wide variety of inference workloads, achieving up to 3x speedup for 8-bit neural networks, and up to 4.8x speedup for binary neural networks, respectively, over the optimized implementations of neural networks today.
Vegetation change over fifty years in humid grasslands of KwaZulu-Natal (Acocks's sites)

Eighty three of Acocks's sites, originally surveyed about 50 years ago, were resurveyed in 1996 to determine the extent of grassland change in the humid grasslands of KwaZulu-Natal. Sites were relocated using 1:10 000 scale ortho-photos and present land cover was determined for each site. Forty six of the sites that were still under original grassland were further examined to determine present species composition. A survey method was designed that would emulate Acocks's data and comparisons were drawn between original and present species composition. These differences were then analysed together with some environmental variables to try to determine the factors which had the most influence on the change and which environment and management factors are related to the present variation in composition among sites. Of the 83 sites, 26 had changed from natural vegetation to some other form of agriculture such as forestry or cultivation. Most of this change had occurred in the Natal Mistbelt Ngongoni Veld where largg areas are forested. Cultivation is found predominantly in the communal areas where subsistence, cultivation practices are employed. The remainder of the sites had changed significantly in terms of their species composition. The most pronounced change had occurred in areas under communal tenure although significant changes had occurred in the commercially farmed areas. The direction of change was also more consistent towards species that commonly predominate in heavily grazed areas in the communal areas compared to the commercial areas. The exact reasons for this were unclear but this could possibly be attributed to heavier^ stocking rates in the communal areas. Change in f loristic composition was also more pronounced at lower altitudes where the mean annual rainfall is lower and the mean annual temperature higher. This could possibly be a result of the
Expert Blogs and Consumer Perceptions of Competing Brands

How and to what extent social media can generate desired benefits for firms has been of great interest to both researchers and practitioners. Extant literature has offered mixed perspectives comprising both optimism and skepticism. Furthermore, research has only begun to examine how social media can bring forth sustainable value for firms beyond sales and a simultaneous consideration of their impacts on a firm as well as its rivals in today’s competitive market remains lacking. In this study, we investigate the competitive effects of social media blog sentiments and brand performances of firms operating within the same industry. We assembled a novel, comprehensive dataset that combined the extent of social media blog valence and volume of competing brands in the personal computer industry and individual consumers’ evaluations of the brands collected at a daily level with 7,871 brand-day observations. Our analyses unveil three key insights: 1) a focal brand’s social media blog sentiment enhances its own brand performances and undermines its competitors’ brand performances in the long run; 2) the focal brand’s blog sentiment has a reinforcing carry-over effect on its own subsequent sentiment and a cannibalistic effect on its competitor brands’ social media blog sentiment; and 3) the positive effect of blog sentiment on brand performances is stronger when the focal brand is a non-leading (versus leading) brand, while the reinforcing effect on social media blog sentiment is stronger when the focal brand is a leading (versus non-leading) brand. The findings advance research by offering a more holistic understanding about the competitive and dynamic effects of social media, enabling firms to gauge what they may gain (or lose) from their own (or competitors’) use of social media.
C ONTENT S HARING IN A S OCIAL B ROADCASTING E NVIRONMENT : E VIDENCE FROM T WITTER 1

The rise of social broadcasting technologies has greatly facilitated open access to information worldwide, not only by powering decentralized information production and consumption, but also by expediting information diffusion through social interactions like content sharing. Voluntary information sharing by users in the context of Twitter, the predominant social broadcasting site, is studied by modeling both the technology and user behavior. A detailed data set about the official content-sharing function on Twitter, called retweet , is collected and the statistical relationships between users’ social network characteristics and their retweeting acts are documented. A two-stage consumption-sharing model is then estimated using the conditional maximum likelihood estimatio (MLE) method. The empirical results convincingly support our hypothesis that weak ties (in the form of unidirectional links) are more likely to engage in the social exchange process of content sharing. Specifically, we find that after a median quality tweet (as defined in the sample) is consumed, the likelihood that a unidirectional follower will retweet is 3.1 percentage point higher than the likelihood that a bidirectional follower will do so.