Miracle-dz/UniFAR-FTUs huggingface dataset:
The complete mitochondrial genome sequence of Lepus tolai in Xinjiang

Abstract Lepus tolai has a wide geographic distribution in the world, and there are some taxonomic confusions due to lack of studies. The complete mitochondrial genome of L. tolai in Xinjiang is 17,047 bp long with 13 protein-coding genes (PCGs), 22 tRNAs, two rRNAs, and a control region. The overall base composition is 31.81% of A, 29.40% of T, 25.67%of C, and 13.12% of G, showing AT-rich. Phylogenetic analysis results showed that L. tolai is closely related to Lepus timidus, and distantly related to Lepus earoupenses and Lepus capensis. The new mtDNA data will supplement the mitochondrial gene pool of Lepus and helpful for validating taxonomic status of L. tolai on mtDNA level.
Tegument Protein BNRF1 Regulation of Epstein-Barr Virus Genome Chromatinization During Early Infection

Epstein-Barr virus (EBV) is a ubiquitously prevalent human herpesvirus whose persistent latent infection is associated with many lymphomas. The prevalence of this virus can be attributed to its ability to establish a persistent latent infection in host cells, during which only a small number of viral genes are expressed from a highly regulated viral genome. However, it is not completely understood how EBV evades cellular antiviral defenses and regulates chromatin assembly to establish latent infections. The EBV major tegument protein BNRF1 was found to be required for the establishment of latent infections, and contains sequence homology to cellular purine biosynthesis enzymes, yet neither the functional mechanism nor link to purine metabolism is known. We have found that BNRF1 interacts with the cellular transcription co-repressor Daxx, and disrupts the binding between Daxx and its interaction partner, the chromatin remodeler ATRX. By ectopically complimenting BNRF1-null virus with mutant BNRF1, we found that the interaction with Daxx is essential for BNRF1 to support viral gene expression and infection. Furthermore, knockdown studies show that Daxx and ATRX are involved in the maintenance of viral chromatin during latency. With the Daxx-ATRX complex recently found to function as a histone variant H3.3 chaperone, we found that BNRF1 forms a complex with Daxx together with histones H3.3 and H4, suggesting potential modulation of a histone pre-deposition complex. In support of this, we show that BNRF1 can increase the release of histone H3.3 into the cellular free histone pool. We then show in primary infection of B lymphocytes that BNRF1-knockdown virus failed to prevent Daxx-ATRX access to the viral chromatin. This results in enriched H3.3 and decreased active histone H3K4me3 markers on the viral DNA, coinciding with deficient expression of viral latent genes. Our findings demonstrate that EBV BNRF1, by interacting with Daxx and displacing ATRX, prevents repressive histone variant H3.3 chromatin formation on viral DNA. Thus, BNRF1 is essential for the formation of viral chromatin permissive for expressing viral latent genes. This is the first demonstration of a viral tegument FGARAT-homology protein involved in the regulation of chromatin assembly. Most importantly, our findings suggest that active manipulation of a histone pre-deposition complex could turn chromatin-based host antiviral resistances into a mechanism of establishing viral latent chromatin. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Cell & Molecular Biology First Advisor Paul M. Lieberman This dissertation is available at ScholarlyCommons: http://repository.upenn. edu/edissertations/1476
A New Capacity-Achieving Private Information Retrieval Scheme With (Almost) Optimal File Length for Coded Servers

In a distributed storage system, private information retrieval (PIR) guarantees that a user retrieves one file from the system without revealing any information about the identity of its interested file to any individual server. In this paper, we investigate an <inline-formula> <tex-math notation="LaTeX">$(N,K,M)$ </tex-math></inline-formula> coded server model of PIR, where each of <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> files is distributed to <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> servers in the form of <inline-formula> <tex-math notation="LaTeX">$(N,K)$ </tex-math></inline-formula> maximum distance separable (MDS) code for some <inline-formula> <tex-math notation="LaTeX">$N>K$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$M>1$ </tex-math></inline-formula>. As a result, we propose a new capacity-achieving <inline-formula> <tex-math notation="LaTeX">$(N,K,M)$ </tex-math></inline-formula> coded linear PIR scheme such that it can be implemented with file length <inline-formula> <tex-math notation="LaTeX">$\frac {K(N-K)}{\gcd (N,K)}$ </tex-math></inline-formula>, which is much smaller than the previous best result <inline-formula> <tex-math notation="LaTeX">$K\left({\frac {N}{\gcd (N,K)}}\right)^{M-1}$ </tex-math></inline-formula>. Notably, among all the capacity-achieving coded linear PIR schemes, we show that the file length is optimal if <inline-formula> <tex-math notation="LaTeX">$M>\big \lfloor \frac {K}{\gcd (N,K)}-\frac {K}{N-K}\big \rfloor +1$ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">$\min (K,N-K)|N$ </tex-math></inline-formula>, and within a multiplicative gap <inline-formula> <tex-math notation="LaTeX">$\frac {\min (K,N-K)}{\gcd (N,K)}$ </tex-math></inline-formula> of a lower bound on the minimum file length otherwise.
Molecular aspects of bacterial nanocellulose biosynthesis

Bacterial nanocellulose (BNC) produced by aerobic bacteria is a biopolymer with sophisticated technical properties. Although the potential for economically relevant applications is huge, the cost of BNC still limits its application to a few biomedical devices and the edible product Nata de Coco, made available by traditional fermentation methods in Asian countries. Thus, a wider economic relevance of BNC is still dependent on breakthrough developments on the production technology. On the other hand, the development of modified strains able to overproduce BNC with new properties – e.g. porosity, density of fibres crosslinking, mechanical properties, etc. – will certainly allow to overcome investment and cost production issues and enlarge the scope of BNC applications. This review discusses current knowledge about the molecular basis of BNC biosynthesis, its regulations and, finally, presents a perspective on the genetic modification of BNC producers made possible by the new tools available for genetic engineering.
Skewness-Based Partitioning in SpatialHadoop

In recent years, several extensions of the Hadoop system have been proposed for dealing with spatial data. SpatialHadoop belongs to this group of projects and includes some MapReduce implementations of spatial operators, like range queries and spatial join. the MapReduce paradigm is based on the fundamental principle that a task can be parallelized by partitioning data into chunks and performing the same operation on them, (map phase), eventually combining the partial results at the end (reduce phase). Thus, the applied partitioning technique can tremendously affect the performance of a parallel execution, since it is the key point for obtaining balanced map tasks and exploiting the parallelism as much as possible. When uniformly distributed datasets are considered, this goal can be easily obtained by using a regular grid covering the whole reference space for partitioning the geometries of the input dataset; conversely, with skewed distributed datasets, this might not be the right choice and other techniques have to be applied. for instance, SpatialHadoop can produce a global index also by means of a Quadtree-based grid or an Rtree-based grid, which in turn are more expensive index structures to build. This paper proposes a technique based on both a box counting function and a heuristic, rooted on theoretical properties and experimental observations, for detecting the degree of skewness of an input spatial dataset and then deciding which partitioning technique to apply in order to improve as much as possible the performance of subsequent operations. Experiments on both synthetic and real datasets are presented to confirm the effectiveness of the proposed approach.
Polarization and partisanship: Key drivers of distrust in media old and new?

Some worry that increased partisanship is lowering trust in the news media, as people increasingly come into contact with cross-cutting news coverage. We use multilevel analysis of online survey data from 35 countries and find that left-right partisans (1) have slightly less trust in the news media in general, (2) slightly higher levels of trust in the news they consume and (3) perceive a larger ‘trust gap’ between the news they use and the rest of the news available within their country. However, we do not find evidence to support the idea that people in more politically polarized countries have less trust in the news, or that the association between partisanship and trust is strengthened in polarized political environments. Although in most cases the relationship between partisanship and trust is weak, it is noticeably stronger in the United States. However, the United States is home to a unique media system, and our analysis highlights the problems of assuming that the processes at work in one relatively well-understood country are playing out in the same way globally.
Brain Functional Networks in Type 2 Diabetes Mellitus Patients: A Resting-State Functional MRI Study

Background Previous diabetes mellitus studies of cognitive impairments in the early stages have focused on changes in brain structure and function, and more recently the focus has shifted to the relationships between encephalic regions and diversification of network topology. However, studies examining network topology in diabetic brain function are still limited. Methods The study included 102 subjects; 55 type 2 diabetes mellitus (T2DM) patients plus 47 healthy controls. All subjects were examined by resting-state functional magnetic resonance imaging (rs-fMRI) scan. According to Automated Anatomical Labeling, the brain was divided into 90 anatomical regions, and every region corresponds to a brain network analysis node. The whole brain functional network was constructed by thresholding the correlation matrices of the 90 brain regions, and the topological properties of the network were computed based on graph theory. Then, the topological properties of the network were compared between different groups by using a non-parametric test. Finally, the associations between differences in topological properties and the clinical indicators were analyzed. Results The brain functional networks of both T2DM patients and healthy controls were found to possess small-world characteristics, i.e., normalized clustering coefficient (γ) > 1, and normalized characteristic path length (λ) close to 1. No significant differences were found in the small-world characteristics (σ). Second, the T2DM patient group displayed significant differences in node properties in certain brain regions. Correlative analytic results showed that the node degree of the right inferior temporal gyrus (ITG) and the node efficiencies of the right ITG and superior temporal gyrus of T2DM patients were positively correlated with body mass index. Conclusion The brain network of T2DM patients has the same small-world characteristics as normal people, but the normalized clustering coefficient is higher and the normalized characteristic path length is lower than that of the normal control group, indicating that the brain function network of the T2DM patients has changed. The changes of node properties were mostly concentrated in frontal lobe, temporal lobe and posterior cingulate gyrus. The abnormal changes in these indices in T2DM patients might be explained as a compensatory behavior to reduce cognitive impairments, which is achieved by mobilizing additional neural resources, such as the excessive activation of the network and the efficient networking of multiple brain regions.
Iterative Estimation of Mutual Information with Error Bounds

Mutual Information (MI) is an established measure for linear and nonlinear dependencies between two variables. Estimating MI is nontrivial and requires notable computation power for high estimation quality. While some estimation techniques allow trading result quality for lower runtimes, this tradeoff is fixed per task and cannot be adjusted. If the available time is unknown in advance or is overestimated, one may need to abort the estimation without any result. Conversely, when there are several estimation tasks, and one wants to budget computation time between them, there currently is no efficient way to adjust it dynamically based on certain targets, e.g., high MI values or MI values close to a constant. In this article, we present an iterative estimator of MI. Our method offers an estimate with low quality near-instantly and improves this estimate in fine grained steps with more computation time. The estimate also converges towards the result of a conventional estimator. We prove that the time complexity for this convergence is only slightly slower than non-iterative estimation. Additionally, with each step our estimator also tightens statistical guarantees regarding the convergence result, i.e., confidence intervals, progressively. These also serve as quality indicators for early estimates and allow to reliably discern between attribute pairs with weak and strong dependencies. Our experiments show that these guarantees can also be used to execute threshold queries faster compared to non-iterative estimation.
Mechanical characterization of functionally graded soft materials with ultrasound elastography

Functionally graded soft materials (FGSMs) with microstructures and mechanical properties exhibiting gradients across a spatial volume to satisfy specific functions have received interests in recent years. How to characterize the mechanical properties of these FGSMs in vivo/in situ and/or in a non-destructive manner is a great challenge. This paper investigates the use of ultrasound elastography in the mechanical characterization of FGSMs. An efficient finite-element model was built to calculate the dispersion relation for surface waves in FGSMs. For FGSMs with large elastic gradients, the measured dispersion relation can be used to identify mechanical parameters. In the case where the elastic gradient is smaller than a certain critical value calculated here, our analysis on transient wave motion in FGSMs shows that the group velocities measured at different depths can infer the local mechanical properties. Experiments have been performed on polyvinyl alcohol (PVA) cryogel to demonstrate the usefulness of the method. Our analysis and the results may not only find broad applications in mechanical characterization of FGSMs but also facilitate the use of shear wave elastography in clinics because many diseases change the local elastic properties of soft tissues and lead to different material gradients. This article is part of the theme issue ‘Rivlin's legacy in continuum mechanics and applied mathematics’.
Transistor Width Effect on the Power Supply Voltage Dependence of α-SER in CMOS 6T SRAM

We present the experimental results on the impact of transistor width modulation and power supply voltage variation on the <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>-soft error rate (SER) in a 65-nm CMOS 6T static random access memory (SRAM) obtained from an accelerated test experiment using an Am-<inline-formula> <tex-math notation="LaTeX">$241~\alpha $ </tex-math></inline-formula>-source. Five 6T cells with various combinations of transistor widths were tested and the results show that nMOS and pMOS widths play a different role on SER. We also found that the transistor width modulation effectiveness is highly dependent on the power supply voltage. In particular, the results show that at around nominal voltages, widening all pMOS while keeping all nMOS minimum sized, is the best way to improve SER. However, at lower voltages the results become completely different, and the best option for an overall SER improvement is to keep all transistors minimum sized.
Offset effect on the S-Bend structure losses and optimization of its size for integrated optics

The S-Bend structures are heavily exploited to join optical components. Reducing the power loss caused by the curve is the main objective in the design step of these components. However integrated optical circuits require S-Bend waveguide to be low loss and compact sized. In this paper, we present a contribution to link the curved structure to the straight waveguide by using the simulated bend function available in the Beam propagation tool of the Rsoft commercial software package. Simulation results confirm that this approach allows a reduction of the size of the curved structure with offset with relatively minimum of losses for photonic field.
Staging of Adrenal Gland and Pancreas Neoplastic Cyst with Ultradiluted Viscum album: Case Report

Many animal adrenal lesions are frequently observed at necropsy and most often are asymptomatic with clinical syndromes that cause hypofunction or hyperfunction of the gland. The objective of this report is to demonstrate the staging of cysts and to report the clinical evolution of the dog that presented pathognomonic lesions of Cushing's Syndrome and developed Adrenal Cyst and a mass in the Pancreas. We concluded that the use of ultradiluted Viscum album in this patient promoted the control and staging of cystic tumor disease, pruritus and improved immunity to date, totaling 22 months of injectable therapy.
Leveraging Bitmap Indexing for Subgraph Searching

Deciding whether a query graph is a subgraph of some other in a very large database of small graphs is a problem of major interest in many application domains. As an example, it arises in the searching for specific molecular substructures in currently available molecular databases, whose sizes may reach levels close to one hundred million. State of the art methods to solve this problem follow a filter-then-verify (FTV) paradigm, where an indexing technique is first used in a filtering stage to obtain result candidates and a subgraph isomorphism algorithm is next applied to the candidates in a verification stage to obtain the final result. Among all the available techniques of the state of the art, two of them have demonstrated better performance when applied to large datasets, namely, the GraphGrepSX (GGSX) and CT-Index (CTI). In this paper, three new indexing techniques, one based on GGSX and two based on CTI, are proposed. In particular, Bitmap GGSX (BM-GGSX) leverages the use of bitmaps in the trie structure used by GGSX to achieve performance gains of around 90% in the filtering stage. Column-Wise CT-Index (CWCTI) exploits a column-wise representation of the fingerprints (bitmaps) used by CT-Index to reduce the filtering times around 80% for small queries (8 edges). Finally, K-Means CT-Index (KMCTI), constructs a binary tree of bitmaps from the CT-Index fingerprints to reach filtering time reductions of around 70% for medium queries (20 edges) and 75% for large queries (40 edges).
Reviewing Municipal Energy System Planning in a Bibliometric Analysis: Evolution of the Research Field between 1991 and 2019

In the context of the energy transition, energy system planning is becoming increasingly relevant for decentralized systems. Motivated by the strong increase of publications on municipal energy system planning (MESP), these studies are subjected to a bibliometric analysis in this paper. The 1235 articles, which are based on the Web of Science database, are examined using the R-tool bibliometrix. The study shows that China is the most important contributor with 225 articles, followed by the USA (205) and Germany (120). Most cross-country collaborations were conducted between China and Canada, focusing mainly on uncertainties in MESP. Among the institutions, the North China Electric Power University is responsible for most articles (42). The core journals on MESP are Energy, Applied Energy, Energy Policy, Energies and Renewable Energy, which published 37% of the 1235 articles. Publications on MESP focus on renewable energies, optimization and hybrid energy systems. Furthermore, district heating seems to be a core topic in MESP and is addressed in three of the top five most cited articles. The demonstration of global research trends in MESP can support researchers in identifying the relevant issues regarding this expanding and transforming research area.
Big POI data integration with Linked Data technologies

Point of Interest (POI) data constitute the cornerstone of any application, service or product even remotely related to our physical surroundings. From navigation applications to social networks, tourism, and logistics, we use POI data to search, communicate, decide and plan our actions. POIs are semantically diverse and spatio-temporally evolving entities, having geographical, temporal and thematic relations. Currently, integrating POI data to increase their coverage, timeliness, accuracy and value is a resource-intensive and mostly manual process, with no specialized software available to address the specic challenges of this task. In this paper, we present an integrated toolkit for transforming, linking, fusing and enriching POI data, and extracting additional value from them. In particular, we demonstrate how Linked Data technologies can address the limitations, gaps and challenges of the current landscape in Big POI data integration. We have built a prototype application that enables users to dene, manage and execute scalable POI data integrationworkows built on top of state-of-the-art software for geospatial Linked Data. The application abstracts and hides away the underlying complexity, automates quality-assured integration, scales eciently for world-scale integration tasks and lowers the entry barrier for end-users. Validated against real-world POI datasets in several application domains, our system has shown great potential to address the requirements and needs of cross-sector, cross-border and cross-lingual integration of Big POI data.
Size reduction of oil shale by attrition scrubbing and its effect on kerogen content

ABSTRACT Size reduction of oil shale is an essential process that allows the liberation of organic-rich constituents from inorganic portions to prepare the oil shale for further beneficiation processes. Grinding by conventional methods was impractical and led to technical and economic problems. In this study, the size reduction of the oil shale was conducted by attrition scrubbing process which seems to be an effective process for cleaning the kerogen surface and its disengagement from associated mineral matter. The statistical design was used to study the significance of soaking time, attrition time, and pH on the product in terms of kerogen and LOI contents. The results indicated that the attrition time is the most significant parameter as the wt% of −2.36 mm reaches about 75% after 120 min of attrition. The effect of pH is insignificant unless the ore has an appreciable amount of carbonate minerals. It is worth mentioning that the kerogen content was improved from 10% to 14% by attrition in acidic media. However, the fine fractions had a low-percentage of loss-on-ignition due to the presence of clay.