Miracle-dz/UniFAR-FTUs huggingface dataset:
Cancer modeling by Transgene Electroporation in Adult Zebrafish (TEAZ)

ABSTRACT Transgenic animals are invaluable for modeling cancer genomics, but often require complex crosses of multiple germline alleles to obtain the desired combinations. Zebrafish models have advantages in that transgenes can be rapidly tested by mosaic expression, but typically lack spatial and temporal control of tumor onset, which limits their utility for the study of tumor progression and metastasis. To overcome these limitations, we have developed a method referred to as Transgene Electroporation in Adult Zebrafish (TEAZ). TEAZ can deliver DNA constructs with promoter elements of interest to drive fluorophores, oncogenes or CRISPR-Cas9-based mutagenic cassettes in specific cell types. Using TEAZ, we created a highly aggressive melanoma model via Cas9-mediated inactivation of Rb1 in the context of BRAFV600E in spatially constrained melanocytes. Unlike prior models that take ∼4 months to develop, we found that TEAZ leads to tumor onset in ∼7 weeks, and these tumors develop in fully immunocompetent animals. As the resulting tumors initiated at highly defined locations, we could track their progression via fluorescence, and documented deep invasion into tissues and metastatic deposits. TEAZ can be deployed to other tissues and cell types, such as the heart, with the use of suitable transgenic promoters. The versatility of TEAZ makes it widely accessible for rapid modeling of somatic gene alterations and cancer progression at a scale not achievable in other in vivo systems. Summary: Here, we developed Transgene Electroporation in Adult Zebrafish (TEAZ), a method that enables researchers to study cancer and metastasis by introducing DNA elements focally into somatic adult tissue.
Multiple Amplify-and-Forward Full-Duplex Relays for Legitimate Eavesdropping

In this paper, we consider a legitimate proactive eavesdropping scenario where a central monitor tries to intercept the information exchanged between a pair of suspicious entities through amplify-and-forward full- duplex relays and a cooperative jammer. Specifically, the eavesdropping relays simultaneously listen to the suspicious transmitter and forward the eavesdropped information to the central monitor. At the same time, the jammer broadcasts the jamming signal to maintain the suspicious data rate below the channel capacity of the central monitor so that the eavesdropped information can be successfully decoded by the central monitor. In this system, we jointly design the relay precoders at the eavesdropping relays and the transmit covariance matrix at the jammer to maximize the eavesdropping rate by a two-layer semi-definite relaxation approach. Simulation results verify the efficiency of our proposed solution and show considerable performance gains over conventional schemes.
Persistent memory and orthogonal persistence: a persistent heap design and its implementation for the Java virtual machine

Current computer systems separate main memory from storage. Programming languages typically reflect this distinction using different representations for data in memory (e.g. data structures, objects) and storage (e.g. files, databases). Moving data back and forth between these different layers and representations compromise both programming and execution efficiency. Recent nonvolatile memory technologies, such as Phase-Change Memory, Resistive RAM, and Magnetoresistive RAM make it possible to collapse main memory and storage into a single layer of persistent memory, opening the way for simpler and more efficient programming abstractions for handling persistence. This Ph.D. thesis introduces a design for the runtime environment for languages with automatic memory management, based on an original combination of orthogonal persistence, persistent memory programming, persistence by reachability, and lock-based failure-atomic transactions. Such design can significantly increase programming and execution efficiency, as in-memory data structures are transparently persistent, without the need for programmatic persistence handling, and removing the need for crossing semantic boundaries. In order to validate and demonstrate the proposed concepts, this work also presents JaphaVM, the first Java Virtual Machine specifically designed for persistent memory. In experimental results using benchmarks and real-world applications, JaphaVM in most cases executed the same operations between one and two orders of magnitude faster than database- and file-based implementations, while requiring significantly less lines of code.
RERE deficiency leads to decreased expression of GATA4 and the development of ventricular septal defects

ABSTRACT Deletions of chromosome 1p36 are associated with a high incidence of congenital heart defects (CHDs). The arginine-glutamic acid dipeptide repeats gene (RERE) is located in a critical region for CHD on chromosome 1p36 and encodes a cardiac-expressed nuclear receptor co-regulator. Mutations affecting RERE cause atrial and ventricular septal defects (VSDs) in humans, and RERE-deficient mice also develop VSDs. During cardiac development, mesenchymal cells destined to form part of the atrioventricular (AV) septum are generated when endocardial cells in the AV canal undergo epithelial-to-mesenchymal transition (EMT) and migrate into the space between the endocardium and the myocardium. These newly generated mesenchymal cells then proliferate to fill the developing AV endocardial cushions. Here, we demonstrate that RERE-deficient mouse embryos have reduced numbers of mesenchymal cells in their AV endocardial cushions owing to decreased levels of EMT and mesenchymal cell proliferation. In the endocardium, RERE colocalizes with GATA4, a transcription factor required for normal levels of EMT and mesenchymal cell proliferation. Using a combination of in vivo and in vitro studies, we show that Rere and Gata4 interact genetically in the development of CHDs, RERE positively regulates transcription from the Gata4 promoter and GATA4 levels are reduced in the AV canals of RERE-deficient embryos. Tissue-specific ablation of Rere in the endocardium leads to hypocellularity of the AV endocardial cushions, defective EMT and VSDs, but does not result in decreased GATA4 expression. We conclude that RERE functions in the AV canal to positively regulate the expression of GATA4, and that deficiency of RERE leads to the development of VSDs through its effects on EMT and mesenchymal cell proliferation. However, the cell-autonomous role of RERE in promoting EMT in the endocardium must be mediated by its effects on the expression of proteins other than GATA4. This article has an associated First Person interview with the first author of the paper. Summary: In the developing atrioventricular canal, RERE promotes endothelial-to-mesenchymal transition and mesenchymal cell proliferation by positively regulating Gata4. Tissue-specific ablation of Rere in the endocardium causes ventricular septal defects.
Reconstructing scenes with mirror and glass surfaces

Planar reflective surfaces such as glass and mirrors are notoriously hard to reconstruct for most current 3D scanning techniques. When treated naïvely, they introduce duplicate scene structures, effectively destroying the reconstruction altogether. Our key insight is that an easy to identify structure attached to the scanner---in our case an AprilTag---can yield reliable information about the existence and the geometry of glass and mirror surfaces in a scene. We introduce a fully automatic pipeline that allows us to reconstruct the geometry and extent of planar glass and mirror surfaces while being able to distinguish between the two. Furthermore, our system can automatically segment observations of multiple reflective surfaces in a scene based on their estimated planes and locations. In the proposed setup, minimal additional hardware is needed to create high-quality results. We demonstrate this using reconstructions of several scenes with a variety of real mirrors and glass.
mRNA transfection by a Xentry-protamine cell-penetrating peptide is enhanced by TLR antagonist E6446

Messenger RNA (mRNA) transfection is a developing field that has applications in research and gene therapy. Potentially, mRNA transfection can be mediated efficiently by cell-penetrating peptides (CPPs) as they may be modified to target specific tissues. However, whilst CPPs are well-documented to transfect oligonucleotides and plasmids, mRNA transfection by CPPs has barely been explored. Here we report that peptides, including a truncated form of protamine and the same peptide fused to the CPP Xentry (Xentry-protamine; XP), can transfect mRNAs encoding reporter genes into human cells. Further, this transfection is enhanced by the anti-malarial chloroquine (CQ) and the toll-like receptor antagonist E6446 (6-[3-(pyrrolidin-1-yl)propoxy)-2-(4-(3-(pyrrolidin-1-yl)propoxy)phenyl]benzo[d]oxazole), with E6446 being >5-fold more potent than CQ at enhancing this transfection. Finally, E6446 facilitated the transfection by XP of mRNA encoding the cystic fibrosis transmembrane regulator, the protein mutated in cystic fibrosis. As such, these findings introduce E6446 as a novel transfection enhancer and may be of practical relevance to researchers seeking to improve the mRNA transfection efficiency of their preferred CPP.
Injecting Lexical Contrast into Word Vectors by Guiding Vector Space Specialisation

Word vector space specialisation models offer a portable, light-weight approach to fine-tuning arbitrary distributional vector spaces to discern between synonymy and antonymy. Their effectiveness is drawn from external linguistic constraints that specify the exact lexical relation between words. In this work, we show that a careful selection of the external constraints can steer and improve the specialisation. By simply selecting appropriate constraints, we report state-of-the-art results on a suite of tasks with well-defined benchmarks where modeling lexical contrast is crucial: 1) true semantic similarity, with highest reported scores on SimLex-999 and SimVerb-3500 to date; 2) detecting antonyms; and 3) distinguishing antonyms from synonyms.
Analysis of the error generated by the voltage output accelerometer using the optimal structure of an artificial neural network

The paper presents an analysis of the upper bound of the dynamic error generated by voltage output accelerometer by using an artificial neural network. The integral-square error criterion was assumed as objective function for the above analysis. The relations for determining the above error were presented and also it was shown that after reaching the steady-state of impulse response of the accelerometer, the relationship between the integral-square error and time is linear. Relationship between the linear equation coefficients on two selected parameters of the mathematical model of accelerometer were determined for the range of this sensor work which is mentioned above. These relations were obtained by polynomial regression which optimal order was determined by means of artificial neural network.
An Analysis of Reported Dangerous Incidents, Exposures, and Near Misses amongst Army Soldiers

Occupational health and safety incidents occurring in the military context are of great concern to personnel and commanders. Incidents such as “dangerous incidents”, “exposures”, and “near misses” (as distinct from injuries, illnesses, and fatalities) indicate serious health and safety risks faced by military personnel, even if they do not cause immediate harm. These risks may give rise to harm in the future, if not adequately addressed, and in some cases the incidents may cause latent harm. The purpose of this study was to ascertain the rates and patterns of incidents of these types reported by full time (ARA) and part time (ARES) Australian Army personnel. A retrospective cohort study was performed using self-reported incident data from the Workplace Health, Safety, Compensation and Reporting (WHSCAR) database over a two-year period. Data were analysed descriptively. Of 3791 such incidents, 3636 (96 percent) occurred in ARA and 155 (4 percent) in ARES personnel, somewhat consistent with the proportions of total army person-years served in each (ARA 93 percent; ARES 7 percent). In ARA, 84 percent of these incident types were exposures, 14 percent near misses, and 2 percent dangerous incidents. In ARES, 55 percent of incidents were exposures, 38 percent near misses, and 7 percent dangerous incidents. Soldiers at the rank of ‘private’ experienced the highest rates of these incident types, in both ARA and ARES. Driving gave rise to more near misses than any other activity, in both populations. Exposures to chemicals and sounds were more common in the ARA than ARES. The ARES reported higher proportions of vehicle near misses and multiple mechanism dangerous incidents than the ARA. The findings of this study can usefully inform development of risk mitigation strategies for dangerous incidents, exposures, and near misses in army personnel.
PROTEIN PHOSHATASE 2A B’α and β Maintain Centromeric Sister Chromatid Cohesion during Meiosis in Arabidopsis1[OPEN]

The acquisition of a single chromosome set by gametes generated during sexual reproduction depends on cohesion proteins that are protected by a phosphatase enzyme complex including the proteins PP2AB′α and β. The correct separation of homologous chromosomes during meiosis I, and sister chromatids during meiosis II, relies on the tight control of the cohesion complex. The phosphorylation and subsequent cleavage of the meiotic recombination protein REC8 (REC8-like family protein [SYN1] in Arabidopsis [Arabidopsis thaliana]), the α-kleisin subunit of the cohesion ring, along the chromosome arms at meiosis I allows crossovers and separation of homologous chromosomes without chromatid dissociation. REC8 continues to localize and function at the centromeres up to metaphase II and, in yeast and vertebrates, is protected from cleavage by means of protein phosphatase 2A (PP2A)-mediated dephosphorylation. Here, we show that, in plants, centromeric sister chromatid cohesion until meiosis II also requires the activity of a PP2A-type phosphatase complex. The combined absence of the regulatory subunits PP2AB′α and PP2AB′β leads to the premature loss of chromosome cohesion in meiosis I. Male meiocytes of the pp2ab′αβ double mutant display premature depletion of SYN1. The PP2AA1 structural and B′α regulatory subunit localize specifically to centromeres until metaphase II, supporting a role for the PP2A complex in the SYN1-mediated maintenance of centromeric cohesion in plant meiosis.
The influence mechanism of goal content on employees' ethical sensitivity

Ethical sensitivity is the initial logical component of ethical behaviour. Only if individuals recognise the ethical problems in a situation can they make ethical judgements and perform ethical behaviours. Ethical sensitivity is affected by many factors. Therefore, to promote the ethical behaviour of employees, it is necessary to explore the key factors of employees' ethical sensitivity. Based on a framework of self-determination theory, this study analyses the effects of goal contents on ethical sensitivity and the mediating role of basic psychological needs. A total of 149 employees were surveyed and the results demonstrate the following: 1) intrinsic goals are positively related to ethical sensitivity; 2) the intrinsic goals and basic psychological needs are significantly positively related; 3) basic psychological needs fully mediate the relationship between intrinsic goals and ethical sensitivity. Finally, the practical contributions of the research and suggestions for future studies are discussed.
Confidence region of singular vectors for high-dimensional and low-rank matrix regression

Let M ∈ Rm1×m2 be an unknown matrix with r = rank(M) ≪ min(m1,m2) whose thin singular value decomposition is denoted by M = UΛV⊤ where Λ = diag(λ1, · · · , λr) contains its non-increasing singular values. Low rank matrix regression refers to instances of estimating M from n i.i. d. copies of random pair {(X, y)} where X ∈ Rm1×m2 is a random measurement matrix and y ∈ R is a noisy output satisfying y = tr(M⊤X) + ξ with ξ being stochastic error independent of X. The goal of this paper is to construct efficient estimator (denoted by Û and V̂) and confidence region of U and V. In particular, we characterize the distribution of dist [ (Û, V̂), (U,V) ] = ‖ÛÛ⊤ −UU‖F + ‖V̂V̂⊤ −VV‖F. We prove the asymptotic normality of properly centered and normalized dist [ (Û, V̂), (U,V) ] with data-dependent centering and normalization when r(m1+m2) 3/2 = o(n/ log n), based on which confidence region of U and V is constructed achieving any pre-determined confidence level asymptotically.
Enhanced Session Table Architecture for Stateful Firewalls

Stateful firewall keeps track of the state of network connections. The performance of stateful firewall determines by both the performance of its session table and the mechanism used for packet filtering. This paper presents a stateful session table architecture then integrates it with Splay tree firewall. Splay tree firewall organizes policy rules in a designated prefix length splay tree data structure, and a collection of hash tables grouped by prefix length. Packet filtering time using Splay tree firewall is essentially reduced through multilevel filtering paths, where unwanted packets are rejected as early as possible. The proposed session table architecture reduces memory space consumption and session operations time, as it uses one hash slot per connection. Keeping all connection related information in one session entry produces additional processing time, particularly for session timeout attribute processing. Our proposed session architecture separates session state and timeout attributes information into different data structures to enhance the overall system performance.
A Twitter Corpus for Hindi-English Code Mixed POS Tagging

Code-mixing is a linguistic phenomenon where multiple languages are used in the same occurrence that is increasingly common in multilingual societies. Code-mixed content on social media is also on the rise, prompting the need for tools to automatically understand such content. Automatic Parts-of-Speech (POS) tagging is an essential step in any Natural Language Processing (NLP) pipeline, but there is a lack of annotated data to train such models. In this work, we present a unique language tagged and POS-tagged dataset of code-mixed English-Hindi tweets related to five incidents in India that led to a lot of Twitter activity. Our dataset is unique in two dimensions: (i) it is larger than previous annotated datasets and (ii) it closely resembles typical real-world tweets. Additionally, we present a POS tagging model that is trained on this dataset to provide an example of how this dataset can be used. The model also shows the efficacy of our dataset in enabling the creation of code-mixed social media POS taggers.
Dynamical properties of partial-discharge patterns

Abstract In this paper, Partial Discharge pattern as an indicator of the fault state of insulation systems of medium voltage overhead lines with covered conductors are described, analyzed, and their dynamical properties are researched. Application of data obtained in natural environment with huge variety of noise interferences, affected by various weather conditions, location and time of the day lead to questioning whether the PD-activity can be considered as a system with emergent-like behaviour. The complexity of obtained data and several signal types are examined and described in this contribution. As a main result, a complexity of signals is researched using approximate entropy, sample entropy, and correlation dimension. Finally, 0-1 test for chaos is used to show chaos of almost all signals and for one signal randomness is detected using newly applied stress test. In this paper, Partial Discharge pattern as an indicator of the fault state of insulation systems of medium voltage overhead lines with covered conductors are described, analyzed, and their dynamical properties are researched. Graphical Abstract In this paper, Partial Discharge pattern as an indicator of the fault state of insulation systems of medium voltage overhead lines with covered conductors are described, analyzed, and their dynamical properties are researched. As a main result, a complexity of signals is researched using approximate entropy, sample entropy, and correlation dimension. Finally, 0-1 test for chaos is used to show chaos of almost all signals and for one signal randomness is detected using newly applied stress test.
A Novel Online Convex Optimization Algorithm Based on Virtual Queues

In this paper, online convex optimization (OCO) problems with time-varying objective and constraint functions are studied from the perspective of an agent who takes actions in real-time. Information about the current objective and constraint functions is revealed only after the corresponding action is already chosen. Inspired by a fast converging algorithm for time-invariant optimization in the very recent work \cite{yu2017simple}, we develop a novel online algorithm based on virtual queues for constrained OCO. Optimal points of the dynamic optimization problems with full knowledge of the current objective and constraint functions are used as a dynamic benchmark sequence. Upper bounds on the regrets with respect to the dynamic benchmark and the constraint violations are derived for the presented algorithm in terms of the temporal variations of the underlying dynamic optimization problems. It is observed that the proposed algorithm possesses sublinear regret and sublinear constraint violations, as long as the temporal variations of the optimization problems are sublinear, i.e., the objective and constraint functions do not vary too drastically across time. The performance bounds of the proposed algorithm are superior to those of the state-of- the-art OCO method in most scenarios.
Workload modeling and prediction for resources provisioning in cloud

The evaluation of resource management policies in cloud environments is challenging since clouds are subject to varying demand coming from users with different profiles and Quality de Service (QoS) requirements. Factors as the virtualization layer overhead, insufficient trace logs available for analysis, and mixed workloads composed of a wide variety of applications in a heterogeneous environment frustrate the modeling and characterization of applications hosted in the cloud. In this context, workload modeling and characterization is a fundamental step on systematizing the analysis and simulation of the performance of computational resources management policies and a particularly useful strategy for the physical implementation of the clouds. In this doctoral thesis, we propose a methodology for workload modeling and characterization to create resource utilization profiles in Cloud. The workload behavior patterns are identified and modeled in the form of statistical distributions which are used by a predictive controller to establish the complex relationship between resource utilization and response time metric. To this end, the controller makes adjustments in the resource utilization to maintain the response time experienced by the user within an acceptable threshold. Hence, our proposal directly supports QoS-aware resource provisioning policies. The proposed methodology was validated through two different applications with distinct characteristics: a scientific application to pulmonary diseases diagnosis, and a web application that emulates an auction site. The performance models were compared with monitoring data through graphical and analytical methods to evaluate their accuracy, and all the models presented a percentage error of less than 10 %. The predictive controller was able to dynamically maintain the response time close to the expected trajectory without Service Level Agreement (SLA) violation with an Mean Absolute Percentage Error (MAPE) = 4.36%.