Miracle-dz/UniFAR-FTUs huggingface dataset:
OXA-253, a Variant of the Carbapenem-Hydrolyzing Class D β-Lactamase OXA-143 in Acinetobacter baumannii

ABSTRACT The carbapenem-hydrolyzing class D β-lactamase OXA-253 was identified in an Acinetobacter baumannii clinical isolate belonging to sequence type 113 (ST113) in Brazil. OXA-253 shares 93.8% amino acid identity with OXA-143. The blaOXA-253 gene is located on a ca. 20-kb plasmid. The genetic environment of the blaOXA-253 gene shares the highest identity with ubiquitous GR2 group plasmids usually carrying blaOXA-24/-40 genes.
Automated di / dt Stressmark Generation for Microprocessor Power Distribution Networks

In this paper, we propose a method for automated di/dt stressmark generation to test maximum voltage droop in a microprocessor power distribution network. The di/dt stressmark is an instruction sequence which draws periodic high and low current pulses that maximize voltage fluctuations including voltage droops. In order to automate di/dt stressmark generation, we devise a code generator with the ability to control instruction sequencing, register assignments, and dependencies. Our framework uses a Genetic Algorithm in scheduling and optimizing candidate instruction sequences to create a maximum voltage droop. The simulation results show that our automatically generated di/dt stressmarks achieved more than 40% average increase in voltage droop compared to hand-coded di/dt stressmarks and typical benchmarks in experiments covering three micro-processor architectures and five power distribution network (PDN) models. Additionally, our method considers all the units in a microprocessor, as opposed to a previous ILP scheduling method that handles only execution units.
Geochemical and geophysical constrains on the dynamic topography of the Southern African Plateau

The deep mantle African Superswell is considered to contribute to the topographic uplift of the Southern African Plateau, but dynamic support estimates vary wildly depending on the approach and data used. One reason for these large disparities is that the role of lithospheric structure, key in modulating deep dynamic contributions to elevation, is commonly ignored or oversimplified in convection studies. We use multiple high‐quality geophysical data coupled with xenolith‐based geochemical constraints to compute the isostatic lithospheric contribution to the elevation of the Plateau, facilitating isolation of the current dynamic component from the total observed elevation. We employ a multiobservable stochastic algorithm to invert geoid anomaly, surface‐wave dispersion data, magnetotelluric data, and surface heat flow to predict elevation in a fully thermodynamically and internally‐consistent manner. We find that a compositionally layered 230 ± 7 km thick lithosphere is required to simultaneously fit all four data types, in agreement with abundant independent xenolith evidence. Our stochastic modeling indicates a lithospheric contribution to elevation of the order of 670 m, which implies dynamic support arising from the convecting sublithospheric mantle of ∼650 m. Our results have important implications for the understanding of lithospheric‐deep mantle feedback mechanisms and for calibrating dynamic topography estimates from global convection studies.
Exploratory mining and pruning optimizations of constrained associations rules

From the standpoint of supporting human-centered discovery of knowledge, the present-day model of mining association rules suffers from the following serious shortcomings: (i) lack of user exploration and control, (ii) lack of focus, and (iii) rigid notion of relationships. In effect, this model functions as a black-box, admitting little user interaction in between. We propose, in this paper, an architecture that opens up the black-box, and supports constraint-based, human-centered exploratory mining of associations. The foundation of this architecture is a rich set of constraint constructs, including domain, class, and SQL-style aggregate constraints, which enable users to clearly specify what associations are to be mined. We propose constrained association queries as a means of specifying the constraints to be satisfied by the antecedent and consequent of a mined association. In this paper, we mainly focus on the technical challenges in guaranteeing a level of performance that is commensurate with the selectivities of the constraints in an association query. To this end, we introduce and analyze two properties of constraints that are critical to pruning: anti-monotonicity and succinctness. We then develop characterizations of various constraints into four categories, according to these properties. Finally, we describe a mining algorithm called CAP, which achieves a maximized degree of pruning for all categories of constraints. Experimental results indicate that CAP can run much faster, in some cases as much as 80 times, than several basic algorithms. This demonstrates how important the succinctness and anti-monotonicity properties are, in delivering the performance guarantee.
Error Estimation for the Linearized Auto-Localization Algorithm

The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs), using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL), the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.
Data-Intensive Supercomputing: The case for DISC

Google and its competitors have created a new class of large-scale computer systems to support Internet search. These “Data-Intensive Super Computing” (DISC) systems differ from conventional supercomputers in their focus on data: they acquire and maintain continually changing data sets, in addition to performing large-scale computations over the data. With the massive amounts of data arising from such diverse sources as telescope imagery, medical records, online transaction records, and web pages, DISC systems have the potential to achieve major advances in science, health care, business efficiencies, and information access. DISC opens up many important research topics in system design, resource management, programming models, parallel algorithms, and applications. By engaging the academic research community in these issues, we can more systematically and in a more open forum explore fundamental aspects of a societally important style of computing.
Enhanced Inhibition of Prostate Tumor Growth by Dual Targeting the Androgen Receptor and the Regulatory Subunit Type Iα of Protein Kinase A in Vivo

Progression to castration resistance is a major problem in the treatment of advanced prostate cancer and is likely to be driven by activation of several molecular pathways, including androgen receptor (AR) and cyclic AMP-dependent protein kinase A (PKA). In this study, we examined the therapeutic efficacy of a combined inhibition of the AR and the regulatory subunit type Iα (RIα) of protein kinase A with second generation antisense oligonucleotides (ODNs) in androgen-sensitive LNCaP and castration-resistant LNCaPabl tumors in vivo. We found that targeting the AR alone inhibited LNCaP, as well as LNCaPabl tumors. Combined inhibition resulted in an improved response over single targeting and even a complete tumor remission in LNCaPabl. Western blot analysis revealed that both ODNs were effective in reducing their target proteins when administered alone or in combination. In addition, treatment with the ODNs was associated with an induction of apoptosis. Our data suggest that dual targeting of the AR and PKARIα is more effective in inhibiting LNCaP and LNCaPabl tumor growth than single treatment and may give a treatment benefit, especially in castration-resistant prostate cancers.
Convergence of Monte Carlo Tree Search in Simultaneous Move Games

We study Monte Carlo tree search (MCTS) in zero-sum extensive-form games with perfect information and simultaneous moves. We present a general template of MCTS algorithms for these games, which can be instantiated by various selection methods. We formally prove that if a selection method is e-Hannan consistent in a matrix game and satisfies additional requirements on exploration, then the MCTS algorithm eventually converges to an approximate Nash equilibrium (NE) of the extensive-form game. We empirically evaluate this claim using regret matching and Exp3 as the selection methods on randomly generated games and empirically selected worst case games. We confirm the formal result and show that additional MCTS variants also converge to approximate NE on the evaluated games.
A Simple Lattice Model That Captures Protein Folding, Aggregation and Amyloid Formation

The ability of many proteins to convert from their functional soluble state to amyloid fibrils can be attributed to inter-molecular beta strand formation. Such amyloid formation is associated with neurodegenerative disorders like Alzheimer's and Parkinson's. Molecular modelling can play a key role in providing insight into the factors that make proteins prone to fibril formation. However, fully atomistic models are computationally too expensive to capture the length and time scales associated with fibril formation. As the ability to form fibrils is the rule rather than the exception, much insight can be gained from the study of coarse-grained models that capture the key generic features associated with amyloid formation. Here we present a simple lattice model that can capture both protein folding and beta strand formation. Unlike standard lattice models, this model explicitly incorporates the formation of hydrogen bonds and the directionality of side chains. The simplicity of our model makes it computationally feasible to investigate the interplay between folding, amorphous aggregation and fibril formation, and maintains the capability of classic lattice models to simulate protein folding with high specificity. In our model, the folded proteins contain structures that resemble naturally occurring beta-sheets, with alternating polar and hydrophobic amino acids. Moreover, fibrils with intermolecular cross-beta strand conformations can be formed spontaneously out of multiple short hydrophobic peptide sequences. Both the formation of hydrogen bonds in folded structures and in fibrils is strongly dependent on the amino acid sequence, indicating that hydrogen-bonding interactions alone are not strong enough to initiate the formation of beta sheets. This result agrees with experimental observations that beta sheet and amyloid formation is strongly sequence dependent, with hydrophobic sequences being more prone to form such structures. Our model should open the way to a systematic study of the interplay between the factors that lead to amyloid formation.
Primary mesenteric gastrointestinal stromal tumour

Primary mesenteric gastrointestinal stromal tumours (GISTs) are rare tumours and can be included as a differential for an expanding intraabdominal mass. We present the case, in our institution, of a 72-year-old male who presented with non-specific symptoms and was diagnosed with a primary mesenteric GIST following resection. We report his follow-up and discuss the current theories as to the origins of these rare tumours and current treatment modalities.
Saccharomyces cerevisiae HMO1 interacts with TFIID and participates in start site selection by RNA polymerase II

Saccharomyces cerevisiae HMO1, a high mobility group B (HMGB) protein, associates with the rRNA locus and with the promoters of many ribosomal protein genes (RPGs). Here, the Sos recruitment system was used to show that HMO1 interacts with TBP and the N-terminal domain (TAND) of TAF1, which are integral components of TFIID. Biochemical studies revealed that HMO1 copurifies with TFIID and directly interacts with TBP but not with TAND. Deletion of HMO1 (Δhmo1) causes a severe cold-sensitive growth defect and decreases transcription of some TAND-dependent genes. Δhmo1 also affects TFIID occupancy at some RPG promoters in a promoter-specific manner. Interestingly, over-expression of HMO1 delays colony formation of taf1 mutants lacking TAND (taf1ΔTAND), but not of the wild-type strain, indicating a functional link between HMO1 and TAND. Furthermore, Δhmo1 exhibits synthetic growth defects in some spt15 (TBP) and toa1 (TFIIA) mutants while it rescues growth defects of some sua7 (TFIIB) mutants. Importantly, Δhmo1 causes an upstream shift in transcriptional start sites of RPS5, RPS16A, RPL23B, RPL27B and RPL32, but not of RPS31, RPL10, TEF2 and ADH1, indicating that HMO1 may participate in start site selection of a subset of class II genes presumably via its interaction with TFIID.
Paravalvular aortic leak after transcatheter aortic valve replacement: current knowledge.

Transcatheter aortic valve replacement (TAVR) is now well-established as the standard of care for patients with severe symptomatic aortic stenosis who are deemed inoperable,1 and is seen as an alternative treatment option to surgical aortic valve replacement (SAVR) in a subset of patients with high postoperative mortality.2 The native valve is typically not removed but instead crushed by the superimposed bioprosthesis, which can result in an incomplete seal of the bioprosthetic valve and aortic annulus, with subsequent occurrence of paravalvular leak (PVL). Two types of Transcatheter Heart Valves (THV) that have been widely used, the balloon-expandable Edwards valve (Cribier-Edwards, Edwards SAPIEN and Edwards SAPIEN XT) by Edwards Lifesciences, and the self-expandable CoreValve by Medtronic, have been described in detail elsewhere.3,4 Despite the evolving technology of transcatheter valves, PVL post-TAVR is common, with a wide range of reported incidences (Table 1). Most importantly, PVL has been associated with increased short- and long-term mortality post-TAVR, and is seen as a barrier to more widespread use of this promising technique.5–13 This article describes the incidence, causes, and predictors of PVL, as well as its impact on clinical outcomes. Methods of prevention, diagnosis, and treatment of PVL are also reviewed. View this table: Table 1. TAVR Studies and Registries Reporting Incidence of PVL in >100 Patients Aortic regurgitation is characterized as either central or paravalvular. Pathological central regurgitation occurs in diseased native valves or damaged prosthetic valves, whereas minor central regurgitation is often a physiological feature of some bioprosthetic valves by virtue of their design. On the other hand, PVL is a complication only of aortic valve prostheses and occurs more commonly post-TAVR (Figure 1) than after SAVR. Figure 1. Parasternal longitudinal axis transthoracic echocardiography view showing mild paravalvular leak post–transcatheter heart valve deployment. Arrow indicates the site of paravalvular leak. Various multicenter …
Incremental entity fusion from linked documents

In many government applications, especially for intelligence and law-enforcement, we often find that information about entities, such as persons or even companies, are available in disparate data sources. For example, information distributed across passports, driving licences, bank accounts, and income tax documents that need to be resolved and fused to reveal a consolidated profile of an individual. In this paper we describe an algorithm to fuse documents that are highly likely to belong to the same entity by exploiting inter-document references in addition to attribute similarity. Our technique uses a combination of iterative graph-traversal, locality-sensitive hashing, iterative match-merge, and graph-clustering to discover unique entities based on a document corpus. Further, new sets of documents can be added incrementally while having to re-process only a small subset of a previously fused entity-document collection. We present performance and quality results via both Bayesian likelihood fusion as well as using Support Vector Machines to demonstrate benefit of using inter-document references, both to improve accuracy as well as for detecting attempts at deliberate obfuscation.
Science in motion: common molecular pathological themes emerge in the hereditary spastic paraplegias

The hereditary spastic paraplegias are a group of neurodegenerative conditions that all share the principal clinical feature of progressive lower limb spastic paralysis, caused by either failure of development or progressive degeneration of the corticospinal tract. The conditions are characterised by extreme genetic heterogeneity, with at least 20 genes involved. Until recently, no functional overlap was apparent in the associated molecular pathological mechanisms. However, with recent progress in hereditary spastic paraplegia gene identification, common pathological themes are now emerging.
Combining semantic and syntactic information sources for 5-w question answering

This paper focuses on combining answers generated by a semantic parser that produces semantic role labels (SRLs) and those generated by syntactic parser that produces function tags for answering 5-W questions, i.e., who, what, when, where, and why. We take a probabilistic approach in which a system’s ability to correctly answer 5-W questions is measured with the likelihood that its answers are produced for the given word sequence. This is achieved by training statistical language models (LMs) that are used to predict whether the answers returned by semantic parse or those returned by the syntactic parser are more likely. We evaluated our approach using the OntoNotes dataset. Our experimental results indicate that the proposed LM-based combination strategy was able to improve the performance of the best individual system in terms of both F1 measure and accuracy. Furthermore, the error rates for each question type were also significantly reduced with the help of the proposed approach. Index Terms: Question answering, Spoken language understanding applications
Writing with a Joystick: A Comparison of Date Stamp, Selection Keyboard, and Edge Write

A joystick text entry method for game controllers and mobile phones would be valuable, since these devices often have joysticks but no conventional keyboards. But prevalent joystick text entry methods are slow because they are selection-based. EdgeWrite, a new joystick text entry method, is not based on selection but on gestures from a unistroke alphabet. Our experiment shows that this new method is faster, leaves fewer errors, and is more satisfying than date stamp and selection keyboard (two prevalent selection-based methods) for novices after minimal practice. For more practiced users, our results show that EdgeWrite is at least 1.5 times faster than selection keyboard, and 2.4 times faster than date stamp.
Effect of Sewage and Industrial Effluents on Bacterial and Archaeal Communities of Creek Sediments in the Taihu Basin

Different characteristics of wastewater have different effects on the diversity and abundance of bacteria and archaea in rivers. There are many creeks around Taihu Lake, and they receive a large volume of industrial wastewater and domestic sewage, which is discharged into these creeks, and finally into Taihu Lake. The present study determined Illumina reads (16S rRNA gene amplicons) to analyze the effects of industrial wastewater and domestic sewage on the bacterial and archaeal communities at the different sampling sites along two creeks. The bacterial and archaeal diversity of the creek receiving sewage was higher than that of the creek receiving industrial waste. Proteobacteria dominated the microbial communities of all samples in both creeks. Betaproteobacteria dominated in the sewage creek, and its abundance declined along the creek. Certain pollutant-resistant classes were more abundant at the site near to the pollution source of the industry creek (e.g., Epsilonproteobacteria and Flavobacteria). Halobacteria belonging to the phylum Euryarchaeota was the dominant archaea at all sites in both creeks, while Methanobacteria was more abundant in the industry creek. The bacterial community was more affected by the distance between the sampling site and the pollutant source than the archaeal community, indicating that bacterial diversity and abundance could be a good index to distinguish domestic and industrial pollution, especially when the main pollution sources are difficult to identify.
Virtual power plants: An answer to increasing distributed generation

In the future an adaptive power system is required to integrate the emerging distributed generation (DG) and renewable energy sources (RES). Since most present power systems are based on active controlled transmission network and passive distribution network, the development of smart grids in the distribution network will facilitate and enhance the growth of DG&RES. To develop smart grids, active control of both distribution network and DG&RES is needed. This research employs the virtual power plant (VPP) concept to develop active control of the present and emerging DG&RES. This paper discusses the impact of DG&RES and highlights the advantages of the VPP concept taking major technical, economical and regulatory aspects in consideration.
Mechanical design of a lightweight compliant and adaptable active ankle foot orthosis

The ankle joint is the main contributor in providing support to the body, ensuring forward progression and initiating the swing of the leg during the push-off phase of walking. However, its capability can be negatively altered by neuromuscular disorders. In these cases, an active ankle-foot orthosis (AAFO) can greatly enhance the rehabilitation of the affected patients. This paper presents the mechanical design of a lightweight and compliant AAFO, which can be used for rehabilitation purposes. The actuator is bidirectional, thus it can assist the ankle during both dorsiflexion and plantarflexion. With respect to most of the existing AAFOs, the presented one is adaptable to different subjects. The connections between the ankle actuator and the user's shank and foot are designed to fit the AAFO to different users and to align the human and the robot ankle joints, without the need of building customized versions of it. The implemented ankle actuator is a MACCEPA (Mechanically Adjustable Compliance and Controllable Equilibrium Position Actuator) and it can provide a peak torque of 25Nm. Due to a careful design of the actuator components, the total weight of the AAFO is only 1.7kg.