Miracle-dz/UniFAR-FTUs huggingface dataset:
Space-optimal heavy hitters with strong error bounds

The problem of finding heavy hitters and approximating the frequencies of items is at the heart of many problems in data stream analysis. It has been observed that several proposed solutions to this problem can outperform their worst-case guarantees on real data. This leads to the question of whether some stronger bounds can be guaranteed. We answer this in the positive by showing that a class of counter-based algorithms (including the popular and very space-efficient <scp>Frequent</scp> and <scp>SpacesSaving</scp> algorithms) provides much stronger approximation guarantees than previously known. Specifically, we show that errors in the approximation of individual elements do not depend on the frequencies of the most frequent elements, but only on the frequency of the remaining tail. This shows that counter-based methods are the most space-efficient (in fact, space-optimal) algorithms having this strong error bound. This tail guarantee allows these algorithms to solve the sparse recovery problem. Here, the goal is to recover a faithful representation of the vector of frequencies, <i>f</i>. We prove that using space <i>O</i>(<i>k</i>), the algorithms construct an approximation <i>f</i>* to the frequency vector <i>f</i> so that the <i>L</i><sub>1</sub> error ∥∥<i>f</i>−∥<i>f</i>*∥<sub>1</sub> is close to the best possible error min<sub><i>f</i>′</sub> ∥<i>f</i>′ − <i>f</i>∥<sub>1</sub>, where <i>f′</i> ranges over all vectors with at most <i>k</i> non-zero entries. This improves the previously best known space bound of about <i>O</i>(<i>k</i> log <i>n</i>) for streams without element deletions (where <i>n</i> is the size of the domain from which stream elements are drawn). Other consequences of the tail guarantees are results for skewed (Zipfian) data, and guarantees for accuracy of merging multiple summarized streams.
T-cell leukemogenesis is an inappropriate lineage decision-making process: implications for precision oncology

ABSTRACT Genetic lineage tracing in cell type-specific mouse models of T-cell acute lymphoblastic leukemia (T-ALL) have revealed that tumor cell identity is imposed by expression of the oncogene Lim Domain Only 2 (LMO2), rather than by the target cell phenotype. This approach allowed to identify that secondary genomic alterations, like Notch1 mutations, appeared late and only took place within the thymus during T-ALL development. These concepts are therefore critical for the development of modern therapies aimed at curing T-ALL.
Loss of Mecp2 Causes Atypical Synaptic and Molecular Plasticity of Parvalbumin-Expressing Interneurons Reflecting Rett Syndrome–Like Sensorimotor Defects

Abstract Rett syndrome (RTT) is caused in most cases by loss-of-function mutations in the X-linked gene encoding methyl CpG-binding protein 2 (MECP2). Understanding the pathological processes impacting sensory-motor control represents a major challenge for clinical management of individuals affected by RTT, but the underlying molecular and neuronal modifications remain unclear. We find that symptomatic male Mecp2 knockout (KO) mice show atypically elevated parvalbumin (PV) expression in both somatosensory (S1) and motor (M1) cortices together with excessive excitatory inputs converging onto PV-expressing interneurons (INs). In accordance, high-speed voltage-sensitive dye imaging shows reduced amplitude and spatial spread of synaptically induced neuronal depolarizations in S1 of Mecp2 KO mice. Moreover, motor learning-dependent changes of PV expression and structural synaptic plasticity typically occurring on PV+ INs in M1 are impaired in symptomatic Mecp2 KO mice. Finally, we find similar abnormalities of PV networks plasticity in symptomatic female Mecp2 heterozygous mice. These results indicate that in Mecp2 mutant mice the configuration of PV+ INs network is shifted toward an atypical plasticity state in relevant cortical areas compatible with the sensory-motor dysfunctions characteristics of RTT.
Diversity and Niche of Archaea in Bioremediation

Bioremediation is the use of microorganisms for the degradation or removal of contaminants. Most bioremediation research has focused on processes performed by the domain Bacteria; however, Archaea are known to play important roles in many situations. In extreme conditions, such as halophilic or acidophilic environments, Archaea are well suited for bioremediation. In other conditions, Archaea collaboratively work alongside Bacteria during biodegradation. In this review, the various roles that Archaea have in bioremediation is covered, including halophilic hydrocarbon degradation, acidophilic hydrocarbon degradation, hydrocarbon degradation in nonextreme environments such as soils and oceans, metal remediation, acid mine drainage, and dehalogenation. Research needs are addressed in these areas. Beyond bioremediation, these processes are important for wastewater treatment (particularly industrial wastewater treatment) and help in the understanding of the natural microbial ecology of several Archaea genera.
Aggregation Algebras

We develop algebras for aggregation and minimisation for weight matrices and for edge weights in graphs. We verify the correctness of Prim’s and Kruskal’s minimum spanning tree algorithms based on these algebras. We also show numerous instances of these algebras based on linearly ordered commutative semigroups.
Geometric Multi-Model Fitting by Deep Reinforcement Learning

This paper deals with the geometric multi-model fitting from noisy, unstructured point set data (e.g., laser scanned point clouds). We formulate multi-model fitting problem as a sequential decision making process. We then use a deep reinforcement learning algorithm to learn the optimal decisions towards the best fitting result. In this paper, we have compared our method against the state-of-the-art on simulated data. The results demonstrated that our approach significantly reduced the number of fitting iterations.
Polydopamine-Assisted Silver Nanoparticle Self-Assembly on Sericin/Agar Film for Potential Wound Dressing Application

Silver nanoparticles (AgNPs) are extensively applied for their broad-spectrum and excellent antibacterial ability in recent years. Polydopamine (PDA) has great advantages for synthesizing large amounts of AgNPs, as it has multiple sites for silver ion binding and phenolic hydroxyl structure to reduce silver ions to AgNPs. Here, we mixed sericin and agar solution and dried at 65 °C to prepare a sericin (SS)/Agar composite film, and then coated polydopamine (PDA) on the surface of SS/Agar film by soaking SS/Agar film into polydopamine solution, subsequently synthesizing high-density AgNPs with the assistance of PDA to yield antibacterial AgNPs-PDA- SS/Agar film. Scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD) spectra indicated the successful synthesis of high-density AgNPs on the surface of PDA-SS/Agar film. PDA coating and AgNPs modification did not affect the structure of sericin and agar. Furthermore, water contact angle, water absorption and mechanical property analysis showed that AgNPs-PDA-SS/Agar film had excellent hydrophilicity and proper mechanical properties. Inhibition zone and growth curve assays suggested the prepared film had excellent and long-lasting antibacterial ability. In addition, it had excellent cytocompatibility on the fibroblast NIH/3T3 cells. The film shows great potential as a novel kind of wound dressing.
Analysis and Improvement of Optimizer for Query Processing on Graph Store

RDF systems are widely used to store public knowledge bases and process SPARQL queries. A large number of such systems have been proposed in the recent literature to provide low latency and high throughput for concurrent query processing over large RDF data. We perform an in-depth analysis on three key components (cardinality estimation, cost model, and plan enumeration) of the query optimizer to reveal the main issues and challenges on the accuracy and performance for traditional approaches. This calls for a rethink of how to build an accurate and fast query optimizer for modern RDF systems. We introduce a type-centric approach to enhance the accuracy of cardinality estimation prominently, which naturally embeds the lineage of correlated query conditions (triple patterns) into existing type system of RDF data. The preliminary results show that our approach greatly improves the accuracy of query optimization by several orders of magnitude compared to state-of-the-art approaches and provides a better overall performance by reducing execution time or optimization time.
Bile Acid Synthesis: From Nature to the Chemical Modification and Synthesis and Their Applications as Drugs and Nutrients

Bile acids (BAs) are amphiphilic molecules with 24 carbon atoms and consist of a hydrophobic and a rigid steroid nucleus, to which are attached a hydrophilic hydroxyl group and a flexible acidic aliphatic side chain. The steroidal core of BAs constitutes a saturated cyclopentanoperhydrophenanthrene skeleton, consisting of three six-membered (A, B, and C) and one five-membered ring (D). Primary BAs are produced in the hepatocytes, while secondary BAs are formed by modifying the primary BAs in the intestinal lumen, i.e., by the reactions of 7α-dehydroxylation and deconjugation of cholic acid (CA) and chenodeoxycholic acid (CDCA). The most important secondary BAs are deoxycholic acid (DCA) and lithocholic acid (LCA). The BAs realize their effects through nuclear farnesoid X receptors (FXRs) and membrane TGR5 receptors. It has been found that BAs are also associated with other receptors such as the vitamin D receptor (VDR), from which the most significant ligand is calcitriol, as well as with pregnane X receptor (PXR) and potentially with the constitutive androstane receptor (CAR), whose ligands are numerous, structurally different xenobiotics that show greater affinity to BAs. The BAs as therapeutic agents (drugs) have the potential to produce beneficial effects in cases of sexually transmitted diseases, primary biliary cirrhosis (PBC), primary sclerosing cholangitis, gallstones, digestive tract diseases, cystic fibrosis, and cancer. Ursodeoxycholic acid (UDCA) was the only drug approved by the US Food and Drug Administration (FDA) for the treatment of PBC. In this paper, the different pathways of bile acid biosynthesis are explained as well as chemical modifications and the synthesis of different keto derivatives of BAs. Also, the effects of BAs on digestion of nutrients, their role as drugs, and, in particular, the emphasis on the hypoglycemic properties of 7α, 12α-dihydroxy−12–keto−5β-cholanic acid in the treatment of diabetes mellitus are examined in detail.
A Review on the Use of Hydroxyapatite-Carbonaceous Structure Composites in Bone Replacement Materials for Strengthening Purposes

Biomedical materials constitute a vast scientific research field, which is devoted to producing medical devices which aid in enhancing human life. In this field, there is an enormous demand for long-lasting implants and bone substitutes that avoid rejection issues whilst providing favourable bioactivity, osteoconductivity and robust mechanical properties. Hydroxyapatite (HAp)-based biomaterials possess a close chemical resemblance to the mineral phase of bone, which give rise to their excellent biocompatibility, so allowing for them to serve the purpose of a bone-substituting and osteoconductive scaffold. The biodegradability of HAp is low (Ksp ≈ 6.62 × 10−126) as compared to other calcium phosphates materials, however they are known for their ability to develop bone-like apatite coatings on their surface for enhanced bone bonding. Despite its favourable bone regeneration properties, restrictions on the use of pure HAp ceramics in high load-bearing applications exist due to its inherently low mechanical properties (including low strength and fracture toughness, and poor wear resistance). Recent innovations in the field of bio-composites and nanoscience have reignited the investigation of utilising different carbonaceous materials for enhancing the mechanical properties of composites, including HAp-based bio-composites. Researchers have preferred carbonaceous materials with hydroxyapatite due to their inherent biocompatibility and good structural properties. It has been demonstrated that different structures of carbonaceous material can be used to improve the fracture toughness of HAp, as they can easily serve the purpose of being a second phase reinforcement, with the resulting composite still being a biocompatible material. Nanostructured carbonaceous structures, especially those in the form of fibres and sheets, were found to be very effective in increasing the fracture toughness values of HAp. Minor addition of CNTs (3 wt.%) has resulted in a more than 200% increase in fracture toughness of hydroxyapatite-nanorods/CNTs made using spark plasma sintering. This paper presents a current review of the research field of using different carbonaceous materials composited with hydroxyapatite with the intent being to produce high performance biomedically targeted materials.
Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches

We consider the task of controlling a quadrotor to hover in front of a freely moving user, using input data from an onboard camera. On this specific task we compare two widespread learning paradigms: a mediated approach, which learns a high-level state from the input and then uses it for deriving control signals; and an end-to-end approach, which skips high-level state estimation altogether. We show that despite their fundamental difference, both approaches yield equivalent performance on this task. We finally qualitatively analyze the behavior of a quadrotor implementing such approaches.
Toward Secure Blockchain-Enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory

In the Internet of Vehicles (IoV), data sharing among vehicles is critical for improving driving safety and enhancing vehicular services. To ensure security and traceability of data sharing, existing studies utilize efficient delegated proof-of-stake consensus scheme as hard security solutions to establish blockchain-enabled IoV (BIoV). However, as the miners are selected from miner candidates by stake-based voting, defending against voting collusion between the candidates and compromised high-stake vehicles becomes challenging. To address the challenge, in this paper, we propose a two-stage soft security enhancement solution: 1) miner selection and 2) block verification. In the first stage, we design a reputation-based voting scheme to ensure secure miner selection. This scheme evaluates candidates’ reputation using both past interactions and recommended opinions from other vehicles. The candidates with high reputation are selected to be active miners and standby miners. In the second stage, to prevent internal collusion among active miners, a newly generated block is further verified and audited by standby miners. To incentivize the participation of the standby miners in block verification, we adopt the contract theory to model the interactions between active miners and standby miners, where block verification security and delay are taken into consideration. Numerical results based on a real-world dataset confirm the security and efficiency of our schemes for data sharing in BIoV.
Factors Associated with the Risk of Developing Coronary Artery Disease in Medicated Patients with Major Depressive Disorder

Background: The aim of this study was to identify factors associated with high Framingham Risk Score (FRS) in medicated patients with major depressive disorder (MDD). Methods: We examined 61 medicated patients with MDD (mean age 37.77 ± 7.67, 90.2% women) and 43 non-depressed controls (mean age 38.26 ± 9.20, 90.7% women). We administered the Hamilton Depression Rating Scale (HAM-D) and measured systolic blood pressure (SBP), diastolic BP (DBP), mean arterial BP (MAP), pulse wave velocity (PWV), intima-media thickness (IMT), interleukin-6 (IL-6) and triglycerides. Results: We found that medicated patients with MDD had significantly higher levels of HAM-D score (p < 0.01), SBP (p = 0.015), MAP (p = 0.037), IL−6 level (p = 0.007), as compared with controls. Medicated patients who remained moderately to severely depressed showed significantly higher SBP (p = 0.049), DBP (p = 0.009), MAP (p = 0.024), IL−6 level (p = 0.019), left PWV (p = 0.004) and average PWV (p = 0.026) than those with mild depression. Multivariate regression showed that the interaction effect between HAM-D score and triglyceride level (p = 0.018) was significantly associated with FRS in medicated patients with MDD. Conclusions: This study highlights that the interaction effect of the severity of depression and the triglyceride level, was a modifiable factor positively associated with high FRS.
Fine-Grain Iterative Compilation for WCET Estimation

Compiler optimizations, although reducing the execution times of programs, raise issues in static WCET estimation techniques and tools. Flow facts, such as loop bounds, may not be automatically found by static WCET analysis tools after aggressive code optimizations. In this paper, we explore the use of iterative compilation (WCET-directed program optimization to explore the optimization space), with the objective to (i) allow flow facts to be automatically found and (ii) select optimizations that result in the lowest WCET estimates. We also explore to which extent code outlining helps, by allowing the selection of different optimization options for different code snippets of the application.
Multiway FPGA partitioning by fully exploiting design hierarchy

In this paper, we present a new integrated synthesis and partitioning method for multiple-FPGA applications. Our approach bridges the gap between HDL synthesis and physical partitioning by fully exploiting the design hierarchy. We propose a novel multiple-FPGA synthesis and partitioning method which is performed in three phases: (1) fine-grained synthesis, (2) functional-based clustering, and (3) hierarchical set-covering partitioning. This method first synthesizes a design specification in a fine-grained way so that functional clusters can be preserved based on the structural nature of the design specification. Then, it applies a hierarchical set-covering partitioning method to form the final FPGA partitions. Experimental results on a number of benchmarks and industrial designs demonstrate that I&slash;O limits are the bottleneck for CLB utilization when applying a traditional multiple-FPGA synthesis method on flattened netlists. In contrast, by fully exploiting the design structural hierarchy during the multiple-FPGA partitioning, our proposed method produces fewer FPGA partitions with higher CLB and lower I&slash;O-pin utilizations.
Bacillus subtilis exhibits MnmC-like tRNA modification activities

ABSTRACT The MnmE-MnmG complex of Escherichia coli uses either ammonium or glycine as a substrate to incorporate the 5-aminomethyl or 5-carboxymethylaminomethyl group into the wobble uridine of certain tRNAs. Both modifications can be converted into a 5-methylaminomethyl group by the independent oxidoreductase and methyltransferase activities of MnmC, which respectively reside in the MnmC(o) and MnmC(m) domains of this bifunctional enzyme. MnmE and MnmG, but not MnmC, are evolutionarily conserved. Bacillus subtilis lacks genes encoding MnmC(o) and/or MnmC(m) homologs. The glycine pathway has been considered predominant in this typical gram-positive species because only the 5-carboxymethylaminomethyl group has been detected in tRNALysUUU and bulk tRNA to date. Here, we show that the 5-methylaminomethyl modification is prevalent in B. subtilis tRNAGlnUUG and tRNAGluUUC. Our data indicate that B. subtilis has evolved MnmC(o)- and MnmC(m)-like activities that reside in non MnmC homologous protein(s), which suggests that both activities provide some sort of biological advantage.
SDN-Based Resource Management for Autonomous Vehicular Networks: A Multi-Access Edge Computing Approach

Enabling HD-map-assisted cooperative driving among CAVs to improve navigation safety faces technical challenges due to increased communication traffic volume for data dissemination and an increased number of computing/storing tasks on CAVs. In this article, a new architecture that combines MEC and SDN is proposed to address these challenges. With MEC, the interworking of multiple wireless access technologies can be realized to exploit the diversity gain over a wide range of radio spectrum, and at the same time, computing/storing tasks of a CAV are collaboratively processed by servers and other CAVs. By enabling NFV in MEC, different functions can be programmed on the server to support diversified AV applications, thus enhancing the server's flexibility. Moreover, by using SDN concepts in MEC, a unified control plane interface and global information can be provided, and by subsequently using this information, intelligent traffic steering and efficient resource management can be achieved. A case study is presented to demonstrate the effectiveness of the proposed architecture.
Attitudes, Perceptions, and Barriers to Research and Publishing Among Research and Teaching Staff in a Nigerian Research Institute

The economic development of any nation is centered on research. Unfortunately, research activities had suffered serious setback in tertiary research institutions in Nigeria. This study explores the attitudes, perceptions and barriers to research and publishing among academic staff in Nigerian Institute of Leather and Science Technology, (NILEST) Zaria Nigeria. A structured self-administered questionnaire was distributed among 130 research and teaching staff at the various Directorates in NILEST. Data are presented in frequencies and percentages for questionnaire responses. Exactly 93.85%of the questionnaires were validated for the study which included 81.15% male and 18.85% female. The participant were researchers (26.23%), lecturers (31.15%), Technologist (20.49%) and Instructors (22.13%). The majority of participant agreed that research is important for the institute (90.98%). A total of 81.15% believed that conducting research should be mandatory for all academic staff. Only 44.26% was self-reported to have ongoing research. Some of the obstacles reported to have prevented research activities included: lack of funding (72.13%), lack of professional mentorship (84.43%) and inadequate research facilities (89.34%). Participants without a single published paper were 54.545%. Some of the reasons given for not having published papers were “no writing experience (95.65%), high publishing fee (79.71%) and long waiting period for peer review (97.10%)”. The suggestions to improve research status by respondents included“ provision of research grants/funds (92.62%), provision of internet facilities (95.10%), mandatory publication (26.23%) and appropriate mentorship (34.43%). Majority of the respondents believed that research is relevant, only a few were engaged in active research and published articles as evidence. It is therefore recommended that policy makers should devise strategies to focus on active research activities in order to achieve the desire research mandate and goal of institutions in the development of the nation’s economy.