Miracle-dz/UniFAR-FTUs huggingface dataset:
A Deep Learning Reconstruction Framework for Differential Phase-Contrast Computed Tomography With Incomplete Data

Differential phase-contrast computed tomography (DPC-CT) is a powerful analysis tool for soft-tissue and low-atomic-number samples. Limited by the implementation conditions, DPC-CT with incomplete projections happens quite often. Conventional reconstruction algorithms face difficulty when given incomplete data. They usually involve complicated parameter selection operations, which are also sensitive to noise and are time-consuming. In this paper, we report a new deep learning reconstruction framework for incomplete data DPC-CT. It involves the tight coupling of the deep learning neural network and DPC-CT reconstruction algorithm in the domain of DPC projection sinograms. The estimated result is not an artifact caused by the incomplete data, but a complete phase-contrast projection sinogram. After training, this framework is determined and can be used to reconstruct the final DPC-CT images for a given incomplete projection sinogram. Taking the sparse-view, limited-view and missing-view DPC-CT as examples, this framework is validated and demonstrated with synthetic and experimental data sets. Compared with other methods, our framework can achieve the best imaging quality at a faster speed and with fewer parameters. This work supports the application of the state-of-the-art deep learning theory in the field of DPC-CT.
Estimating the benefit of well-managed protected areas for threatened species conservation

Abstract Protected areas are central to global efforts to prevent species extinctions, with many countries investing heavily in their establishment. Yet the designation of protected areas alone can only abate certain threats to biodiversity. Targeted management within protected areas is often required to achieve fully effective conservation within their boundaries. It remains unclear what combination of protected area designation and management is needed to remove the suite of processes that imperil species. Here, using Australia as a case study, we use a dataset on the pressures facing threatened species to determine the role of protected areas and management in conserving imperilled species. We found that protected areas that are not resourced for threat management could remove one or more threats to 1,185 (76%) species and all threats to very few (n = 51, 3%) species. In contrast, a protected area network that is adequately resourced to manage threatening processes within their boundary could remove one or more threats to almost all species (n = 1,551; c. 100%) and all threats to almost half (n = 740, 48%). However, 815 (52%) species face one or more threats that require coordinated conservation actions that protected areas alone could not remove. This research shows that investing in the continued expansion of Australia's protected area network without providing adequate funding for threat management within and beyond the existing protected area network will benefit few threatened species. These findings highlight that as the international community expands the global protected area network in accordance with the 2020 Strategic Plan for Biodiversity, a greater emphasis on the effectiveness of threat management is needed.
Dimension Reduction Techniques for Market Basket Analysis

Market basket analysis helps us to discover which group of items tends to be purchased together by customers. This is a powerful tool in data mining to understand the purchase behavior. Today the data sizes in the datasets of market basket have increased from gigabytes to terabytes or even larger due to which the complexity of analysis of huge datasets has been a major concern in almost all areas of technology in the past decade. A solution to this crucial problem in distributed data mining is that, the massive dataset can be collected and warehoused in a single site if its dimensionality is reduced. Today many dimension reduction algorithms are there and they are generally classified into feature selection, feature extraction and random projection. In this paper a new dimension reduction algorithm is proposed, which is different from all the existing methods, to encode the transactions which reduces the size of transaction that in turn reduces the communication cost and communication bandwidth.
Polymer translocation through nano-pores: influence of pore and polymer deformation

We have simulated polymer translocation across the a α-hemolysin nano-pore via a coarse grained computational model for both the polymer and the pore. We simulate the translocation process by allowing the protein cross a free-energy barrier from a metastable state, in the presence of thermal fluctuations. The deformation in the channel, which we model by making the radius of pore change from large to small size, can be originated by the random and non-random (systematic) cellular environment, drive out the polymer out of equilibrium during the transport dynamics. We expect that in more realistic conditions, effects originating on the translocation phenomena due to the deformability of the nano-pore can either decrease or increase the transport time of biomolecule passing through the channel. Deformation in channel can occurred because the structure of α-hemolysin channel is not completely immobile, hence a small pore deformation can be occurred during translocation process. We also discuss the effects of polymer deformation on the translocation process, which we achieve by varying the value of the empirical and dihedral potential constants. We investigate the dynamic and thermodynamical properties of the translocation process by revealing the statistics of translocation time as a function of the pulling inward force acting along the axis of the pore under the influence of small and large pore. We observed that a pore with small size can speed down the polymer translocation process, especially at the limit of small pulling force. A drastic increase in translocation time at the limit of low force for small pore clearly illustrate the strong interaction between the transport polymer and pore. Our results can be of fundamental importance for those experiments on DNA-RNA sorting and sequencing and drug delivery mechanism for anti-cancer therapy.
Token Exchange Games

Human societies engage in a number of games which use tokens as a means to allocate, issue and access gated resources and property rights: The notion of exchanging tokens that represent and carry value from the past into the future to facilitate economic exchange is a fundamental concept. As agents exchange tokens a network structure is created in which the tokens move from agent to agent. Agents form the vertices in the network and the exchange of tokens creates the link structure. The rules of exchange adopted collectively by agents shape the network structure and affect the distribution of tokens amongst agents. Many inventions including banking, payments networks and blockchain technology have been created for the purpose of keeping accurate records of these implicit networks. However, our formal understanding of tokenised systems as large scale, iterative, interacting structures is limited. The aim of this paper is to study the dynamics of token exchanges as a game, and introduce a mathematical framework for understanding ledgers as complex networks.
Supplementation of Holstein dairy calves fed two levels of crude protein with methionine and lysine

This study aimed to investigate various levels of crude protein (CP) in starter diets and their supplementation with amino acids (AAs) on efficiency, health, and serum metabolites of dairy calves. Ninety-six newborn Holstein calves were allocated to eight treatments, namely T1) 18% CP unsupplemented starter, T2) T1 supplemented with additional 20% methionine, T3) T1 with additional 20% lysine and 20% methionine, T4) T1 with additional 20% lysine, T5) 22% CP unsupplemented starter, T6) T5 supplemented with additional 20% methionine, T7) T5 supplemented with additional 20% lysine and 20% methionine, and T8) T5 supplemented with additional 20% lysine. Consumption of the starter was not influenced by the level of CP. Calves that received the unsupplemented 22% CP starter had higher average daily gain (ADG) and final weight. But no significant differences among diets were found in feed efficiency. Skeletal growth did not exhibit a clear trend. Calves that received T3 had fewer bouts of diarrhea and reduced body temperature. However, there were no significant dietary effects on immunoglobin G (IgG) or total protein concentration in blood. T1–T3 decreased serum urea concentration. Thus, use of T3 resulted in an improved amino acid balance, and was less expensive than the 22% CP starter.Keywords: amino acid, feed intake, immunity, pre-ruminant calf
Multi-Source Weak Supervision for Saliency Detection

The high cost of pixel-level annotations makes it appealing to train saliency detection models with weak supervision. However, a single weak supervision source usually does not contain enough information to train a well-performing model. To this end, we propose a unified framework to train saliency detection models with diverse weak supervision sources. In this paper, we use category labels, captions, and unlabelled data for training, yet other supervision sources can also be plugged into this flexible framework. We design a classification network (CNet) and a caption generation network (PNet), which learn to predict object categories and generate captions, respectively, meanwhile highlight the most important regions for corresponding tasks. An attention transfer loss is designed to transmit supervision signal between networks, such that the network designed to be trained with one supervision source can benefit from another. An attention coherence loss is defined on unlabelled data to encourage the networks to detect generally salient regions instead of task-specific regions. We use CNet and PNet to generate pixel-level pseudo labels to train a saliency prediction network (SNet). During the testing phases, we only need SNet to predict saliency maps. Experiments demonstrate the performance of our method compares favourably against unsupervised and weakly supervised methods and even some supervised methods.
The eukaryotic Initiation Factor 6 (eIF6) regulates ecdysone biosynthesis by modulating translation in Drosophila

During development, ribosome biogenesis and translation reach peak activities, due to impetuous cell proliferation. Current models predict that protein synthesis elevation is controlled by transcription factors and signalling pathways. Developmental models addressing translation factors overexpression effects are lacking. Eukaryotic Initiation Factor (eIF6) is necessary for ribosome biogenesis and efficient translation. eIF6 is a single gene, conserved from yeasts to mammals, suggesting a tight regulation need. We generated a Drosophila melanogaster in vivo model of eIF6 upregulation, demonstrating a boost in general translation and the shut off of the ecdysone biosynthetic pathway. Translation modulation in S2 cells showed that translational rate and ecdysone biosynthesis are inversely correlated. In vivo, eIF6-driven alterations delayed programmed cell death (PCD), resulting in aberrant phenotypes, partially rescued by ecdysone administration. Our data show that eIF6 triggers a translation program with far-reaching effects on metabolism and development, stressing the driving and central role of translation.
Tradeoffs and cultural diversity

Culture is humanity’s prime adaptation. Which cultural traits contribute to adaptive value at the level of cultural groups, and how they do so, is, however, unclear and debated. Here, we apply an approach from systems biology, known as Pareto task inference (ParTI), to bring a fresh perspective to these questions. ParTI considers systems that need to perform multiple tasks. No system can be optimal at all tasks at once, leading to a fundamental tradeoff. These tradeoffs result in specific patterns in multivariate trait data: data falls inside polygons in trait space, whose vertices are trait combinations that are adaptive for each of the tasks. ParTI can infer the number of adaptive tasks and their nature without need for a-priori assumptions, based on the vertices of these polygons. Here, we applied ParTI to two datasets of cultural traits, on Austronesian cultures and modern hunter-gatherers, adjusting for phylogeny and spatial diffusion effects. We find evidence that these independent datasets show a tradeoff between the same three tasks. We identify the tasks as resource defense, resource competition, and mobility/exchange. Specific combinations of cultural traits are adaptive for each of these tasks. This approach can be widely applied to any large multivariate dataset to study trade-offs in cultural evolution.
Novel microsatellite markers for the analysis of Phytophthora capsici populations and Host Resistance for Management of Phytophthora Blight of Pepper

PARADA ROJAS, CAMILO HUMBERTO. Novel Microsatellite Markers for the Analysis of Phytophthora capsici Populations and Host Resistance for Management of Phytophthora Blight of Pepper. (Under the direction of Dr. Lina Quesada). Phytophthora blight (caused by Phytophthora capsici) is an important disease with a broad host range including Solanaceous, Cucurbitaceous, and Fabaceous crops. Despite its impact in vegetable production, P. capsici population structure in North Carolina (NC) is unknown. The release of the P. capsici genome allows for design of robust markers for genetic studies. We identified and characterized simple sequence repeats (SSRs) in the P. capsici transcriptome. A subset of 50 SSR were assayed in a diverse set of P. capsici isolates and evaluated for polymorphism. Polymorphic SSRs were confirmed by fragment analysis and 11 were used for population characterization of 30 P. capsici isolates from different states, hosts, mating types, and fungicide sensitivities. Analysis of genetic relationship among isolates revealed significant geographic structure by state and even by field. Our findings highlight the usefulness of the 11 SSRs to characterize the population structure of P. capsici and potential transferability to closely-related Phytophthora spp. since markers are located in coding regions. This study is a step towards understanding the genetic structure of P. capsici populations, which may assist in deployment of disease management strategies. In that context, we also improved management of Phytophthora blight in peppers by evaluating resistance of commercial and experimental lines of peppers in the greenhouse and the field to P. capsici. Field trials were conducted over the summers of 2015 and 2016 to evaluate 32 commercial and experimental pepper cultivars against a mixed isolate inoculum in NC. Cultivars Martha-R, Meeting, and Paladin were classified as highly resistant and resistant to P. capsici. Tolerance to P. capsici in the field was observed in Fabuloso, Revolution, and Vanguard among other cultivars. Greenhouse experiments were conducted to determine the response of 48 pepper cultivars when inoculated with two isolates from NC and an isolate from Michigan individually. Isolates exhibited different levels of virulence to the pepper cultivars screened for P. capsici resistance. Land races CM334, Fidel, and cultivars Martha-R, Meeting, and Intruder were highly resistant and resistant to all isolates tested. Overall, highly resistant cultivars tended to respond similarly to field inoculations with an isolate mix and greenhouse single isolate inoculations. Our results highlight the importance of screening for resistance with diverse isolates and understanding regional P. capsici populations for better deployment of durable pepper resistance.
The Impact of VEPH1 on Ovarian Cancer Tumour Progression in a Xenograft Mouse Model

Epithelial ovarian cancer has the greatest death to incidence ratio of all gynecological cancers in Canada. The FoxO, TGF-β, and Hippo signalling pathways are implicated in ovarian tumourigenesis; ventricular zone-expressed PH domain protein (Veph1) may be a novel modulator of these pathways. This thesis addresses the objectives of determining the physiological murine tissue expression of Veph1A/B isoforms, and establishing the effect of Veph1 expression on ovarian tumourigenesis. Veph1A and Veph1B transcripts were identified in whole embryos; whereas, only Veph1A transcripts were present in adult tissues. Veph1 expression significantly reduced tumour growth rate in a xenograft mouse model. This was associated with reduced microvessel density and increased necrotic tumour area with no effect on proliferation index. This study suggests that Veph1 may be involved in angiogenesis. Future investigation regarding the effect of Veph1 expression on metastases and ascites formation will be necessary to establish its role in ovarian tumourigenesis and survival.
Reconciling S-LDSC and LDAK models and functional enrichment estimates

Recent work has highlighted the importance of accounting for linkage disequilibrium (LD)-dependent genetic architectures in analyses of heritability, motivating the development of the baseline-LD model used by stratified LD score regression (S-LDSC) and the LDAK model. Although both models include LD-dependent effects, they produce very different estimates of functional enrichment (with larger estimates using the baseline-LD model), leading to different interpretations of the functional architecture of complex traits. Here, we perform formal model comparisons and empirical analyses to reconcile these findings. First, by performing model comparisons using a likelihood approach, we determined that the baseline-LD model attains likelihoods across 16 UK Biobank traits that are substantially higher than the LDAK model. Second, we determined that S-LDSC using a combined model (unlike methods that use the LDAK or baseline-LD models) produces robust enrichment estimates in simulations under both the LDAK and baseline-LD models, validating the combined model as a gold standard. Third, in analyses of 16 UK Biobank traits, we determined that enrichment estimates obtained by S-LDSC using the combined model were nearly identical to those obtained by S-LDSC using the baseline-LD model (concordance correlation coefficient ρc = 0.99), but were larger than those obtained using LDAK (ρc = 0.54). Notably, LDAK enrichment estimates were much higher for a non-default version of LDAK that models SNPs in perfect LD differently by assigning non-zero weights to all SNPs. Our results support the use of the baseline-LD model and confirm the existence of functional annotations that are highly enriched for complex trait heritability.
Natural history of the social millipede Brachycybe lecontii Wood, 1864

Abstract The millipede Brachycybe lecontii Wood, 1864 is a fungivorous social millipede known for paternal care of eggs and forming multi-generational aggregations. We investigated the life history, paternal care, chemical defence, feeding and social behaviour of B. lecontii and provided morphological and anatomical descriptions, using light and scanning electron microscopy. Based on observations of B. lecontii from 13 locations throughout its distribution, we report the following natural history aspects. The oviposition period of B. lecontii lasted from mid-April to late June and the incubation period lasted 3–4 weeks. Only males cared for the eggs and subsequent care of juveniles was not observed. In one case, the clutches of two males became combined and they were later cared for by only one of the males. The defensive compound of B. lecontii is stored in large glands occupying a third of the paranotal volume and were observed only in stadia II millipedes and older. We observed B. lecontii feeding on fungi of the order Polyporales and describe a cuticular structure on the tip of the labrum that may relate to fungivory. We found that their stellate-shaped aggregations (pinwheels) do not form in the absence of fungus and suggest the aggregation is associated with feeding. We describe and illustrate a previously undescribed comb-like structure on the tibia and tarsi of the six anterior-most leg-pairs and measure the colour and spectral reflectance of the B. lecontii exoskeleton.
Neural Coding of Noisy and Reverberant Speech in Human Auditory Cortex

Speech communication in daily listening environments is complicated by the phenomenon of reverberation, wherein any sound reaching the ear is a mixture of the direct component from the source and multiple reflections off surrounding objects and the environment. The brain plays a central role in comprehending speech accompanied by such distortion, which, frequently, is further complicated by the presence of additional noise sources in the vicinity. Here, using magnetoencephalography (MEG) recordings from human subjects, we investigate the neural representation of speech in noisy, reverberant listening conditions as measured by phase-locked MEG responses to the slow temporal modulations of speech. Using systems-theoretic linear methods of stimulus encoding, we observe that the cortex maintains both distorted and distortion-free (cleaned) representations of speech. Also, we show that, while neural encoding of speech remains robust to additive noise in absence of reverberation, it is detrimentally affected by noise when present along with reverberation. Further, using linear methods of stimulus reconstruction, we show that theta-band neural responses are a likely candidate for the distortion free representation of speech, whereas delta band responses are more likely to carry non-speech specific information regarding the listening environment.
Winter Wheat Yield Gaps and Patterns in China

Wheat (Triticum aestivum L.) yield stagnation has been reported in some regions of the world. China is the largest producer of wheat across the globe, but the pattern of its wheat yield stagnation remains poorly addressed. Here, our goal is to examine the temporal trends and spatial patterns of wheat yields along with possible causes based on a comprehensive assessment of winter wheat yield throughout China over the 31-yr period from 1980 to 2010. Combined with the Agricultural Production Systems Simulator (APSIM) wheat model, we assessed the winter wheat yield gaps and patterns in 1414 counties and at five physiogeographic regional scales across China to ascertain the driving factors of yield variations. Wheat yields increased in 53% of the 1414 counties, but the remaining counties experienced yields that never improved, stagnated, or collapsed from 1980 to 2010. The yield gap analysis showed that actual yields represented only 59% of the national average yield potential, indicating a substantial opportunity to improve winter wheat yields. Relatively larger yield gaps were observed in the northern China Plain (NC, 47%) and in southwestern China (SW, 45%). Although the yield gaps in these regions were accompanied by significantly progressive uptrends of actual yields, our results suggest that agronomic management could be further improved. Moreover, underperforming regions could potentially benefit from new investments and strategies to reliably increase actual yields and reverse trends in stagnation in winter wheat performance.