Miracle-dz/UniFAR-FTUs huggingface dataset:
Learn&Fuzz: Machine learning for input fuzzing

Fuzzing consists of repeatedly testing an application with modified, or fuzzed, inputs with the goal of finding security vulnerabilities in input-parsing code. In this paper, we show how to automate the generation of an input grammar suitable for input fuzzing using sample inputs and neural-network-based statistical machine-learning techniques. We present a detailed case study with a complex input format, namely PDF, and a large complex security-critical parser for this format, namely, the PDF parser embedded in Microsoft's new Edge browser. We discuss and measure the tension between conflicting learning and fuzzing goals: learning wants to capture the structure of well-formed inputs, while fuzzing wants to break that structure in order to cover unexpected code paths and find bugs. We also present a new algorithm for this learn&fuzz challenge which uses a learnt input probability distribution to intelligently guide where to fuzz inputs.
Human herpesvirus type 8 infection in an area of Northern Italy with high incidence of classical Kaposi's sarcoma

Previous studies have reported a large variation in the incidence of classical Kaposi's sarcoma across different Districts of the province of Mantua (Northern Italy). To assess whether such differences might be explained by different anti‐HHV8 antibody prevalence, a serological study was conducted in 343 healthy elderly individuals resident in two adjacent Districts, at the highest and the lowest classical Kaposi's sarcoma incidence rate, respectively. Qualitative and quantitative determinations of IgG antibodies against both latent and lytic HHV‐8 antigens were performed by indirect immunofluorescence assay. The assay's sensitivity was studied in 26 patients with classical Kaposi's sarcoma. Overall, anti‐HHV8 antibodies were detected in 25 out of 26 patients (96%), confirming the high sensitivity of this assay. The prevalence of anti‐HHV‐8 antibodies was higher among individuals living in the District had a high incidence of classical Kaposi's sarcoma compared to those living in the District with low incidence (19.4% vs 9.8%, and 15.9% vs 8%; P < 0.05, for latent and lytic antibodies, respectively). Anti‐lytic antibody GMT was higher in people living in the District at high incidence rate compared to those of the other area (328.9 vs. 180.4; P < 0.01). A higher prevalence of HHV‐8 infection was found among persons living in municipalities surrounded by watercourses (OR 2.2, 95% CI: 1.10–4.32). In conclusion, variation in HHV‐8 prevalence appears to explain differences in the incidence rates of classical Kaposi's sarcoma observed in different areas of the province. J. Med. Virol. 76:571–575, 2005. © 2005 Wiley‐Liss, Inc.
Dynamic reconfigurable bit-parallel architecture for large-scale regular expression matching

In this paper, we propose a novel FPGA-based architecture for large-scale regular expression matching, called dynamic reconfigurable bit-parallel NFA architecture (Dynamic BP-NFA) that allows dynamic reconfiguration of the patterns using bit-parallel NFA-simulation. This is the first dynamic reconfigurable FPGA-based hardware with guaranteed performance for the class of extended patterns, where an extended pattern is a restricted regular expression in linear form consisting of letters, classes of letters, don't cares, optional letters, bounded and unbounded length gaps and repeatable letters. The key to our architecture is the use of bit-parallel pattern matching approach that has been developed in string matching communities for the decades. In this approach, the information of an input NFA is compactly encoded in bit-masks stored in a collection of registers and block RAMs. Then, the NFA is efficiently simulated by a fixed circuitry using a combination of bit- and arithmetic-operations on these bit-masks consuming one input letter per clock. As compared with the previous approaches of DFA-based dynamic reconfigurable architectures, experimental results show that the proposed architecture achieves higher throughput for the class of exact string patterns and comparable for the class of extended patterns.
Fistula first initiative: advantages and pitfalls.

### Vascular Access Care before 1997 The arteriovenous fistula (AVF) was first described and used as a reliable form of hemodialysis (HD) vascular access (VA) by Brescia et al. (1) in 1966. Improvements in dialysis technology and the expansion of dialysis eligibility ( e.g. , inclusion of patients with diabetes) resulted in a rapid growth of the ESRD population. Many of these patients benefited from the development of prosthetic grafts when autogenous AVF were not feasible (2–5). In the mid-1980s, permanent catheters (central venous catheters [CVC]) in the internal jugular vein became a means of prolonging temporary access (6–8) and dramatically increased in use. The cumulative effect was a reduction in AVF use and an increase in graft and CVC use in the 1990s. This was associated with increased patient care costs; for example, up to 73% of patients were hospitalized to initiate dialysis and almost invariably had a temporary CVC inserted. VA was a major cause of morbidity and mortality (9), with HD access failure accounting for the most frequent cause of hospitalizations (10) and complications accounting for 14% of all ESRD expenses ($1 billion annually) (9). ### 1997 to 2003: Critical Events That Affected VA Care In an effort to improve VA outcomes, the National Kidney Foundation published the Kidney Disease Outcomes Quality Initiative (K/DOQI) Clinical Practice Guidelines for Vascular Access in 1997. The goal was to optimize management of VA through a set of evidence- and opinion-based based guidelines (10). In the following year, Centers for Medicare and Medicaid Services (CMS; the government-reimbursement agency for Medicare-insured patients) developed ESRD clinical performance measures (CPM) based on the K/DOQI VA guidelines, in response to the Balanced Budget Act of 1997 (11). VA-related CPM include ( 1 ) the proportion of HD patients with AVF, ( 2 ) the proportion of HD patients with a CVC, and ( 3 ) monitoring arteriovenous grafts for stenosis. The overriding goal …
Cembranoids from a Chinese Collection of the Soft Coral Lobophytum crassum

Ten new cembrane-based diterpenes, locrassumins A–G (1–7), (–)-laevigatol B (8), (–)-isosarcophine (9), and (–)-7R,8S-dihydroxydeepoxysarcophytoxide (10), were isolated from a South China Sea collection of the soft coral Lobophytum crassum, together with eight known analogues (11–18). The structures of the new compounds were determined by extensive spectroscopic analysis and by comparison with previously reported data. Locrassumin C (3) possesses an unprecedented tetradecahydrobenzo[3,4]cyclobuta[1,2][8]annulene ring system. Compounds 1, 7, 12, 13, and 17 exhibited moderate inhibition against lipopolysaccharide (LPS)-induced nitric oxide (NO) production with IC50 values of 8–24 μM.
Safety of anticonvulsant agents in pregnancy

Introduction: Seizures in pregnancy are particularly challenging, as their management requires careful consideration of not only the etiology of the seizure, but also the physiologic changes of pregnancy as well as potential adverse effects on the developing embryo or fetus. Newer antiepileptic drugs (AEDs) have increasingly shown promising results of lower rate of teratogenesis, as well as better seizure control during pregnancy. Areas covered: We performed a review of the scientific literature of seizures in pregnancy including status epilepticus as well as eclampsia, with a focus on safety of currently used AEDs. This covers the different generations of antiepileptic medications, their interactions and seizure recurrence preventative measures. In addition, we summarized our personal approach to the care for these women. Expert opinion: In summary, morbidity associated with seizure in pregnancy is decreasing as treatments and supportive therapies have improved. The understanding of teratogenesis as well as novel targeted therapeutics will allow women on AEDs during their pregnancy, to receive the safest drug for their developing fetus as well as themselves.
Function Computation over Heterogeneous Wireless Sensor Networks

The problem of function computation in large scale heterogeneous wireless sensor networks (WSNs) is studied. Suppose n sensors are placed in a disk network area with radius nα, where α is a positive constant. The sensors are located heterogeneously around the sink node, i.e, the density of sensors decreases as the distance from the sink node increases. At one instant, each sensor is assigned an input bit. The target of the sink is to compute a function f of the input bits, where f is either a symmetric or the identity function. Energy-efficient algorithms based on inhomogeneous tessellation of the network are designed and the corresponding optimal energy consumption scaling laws are derived. We show that the proposed algorithms are indeed optimal (except for some polylogarithmic terms) by deriving matching lower bounds on the energy consumption required to compute f. At last, based on the results obtained in this paper as well as those obtained by previous works, some discussions and comparisons are presented. We observe that 1) the heterogeneity extent has a great impact on the computation of both symmetric function and identity function, and 2) the energy usage of computing symmetric function can be significantly smaller than that of computing identity function under certain parameter condition, i.e, performing in-network computation helps save energy.
Efficient models for non-quasi-static effects and correlated noise in SiGe HBTs

The capability of a single CR sub-circuit to model a wide range of non-quasi-static (NQS) delays in silicon germanium heterojunction bipolar transistors is explored. A comparative study is carried out to show that the suitable use of a single CR sub-circuit following the partitioned-charge-based approach can replace the popularly used CR-LCR combination to model both the input and output NQS effects. Based on this NQS model, a correlated noise model is developed, which requires only three additional nodes for implementation in Verilog-A. Results show excellent agreement with numerically simulated data.
Proteomics is the studyof protein expression and function on a genome-wide scale and its application in psychiatric research is relativelynew

The translation of genetic information to proteins forms the basis for most metabolic processes in the body. When these molecules are required, genes are transcribed first to the corresponding messenger ribonucleic acids (mRNAs) and then translated to their protein counterparts. Additional protein diversity is introduced by subsequent processes of post-translational modification (e.g. phosphorylation, glycosylation), resulting in the biological phenotype. This process of transcription, translation and post-translational modification is variable, depending on genetic predispositions and environmental interactions. Thus, the previous notion that one gene results in one protein no longer holds true. Indeed it has been estimated that, if the human genome contains 30 000 expressed genes, there may be the potential to express as many as one million different proteins. Bearing this in mind, the prospect of identifying what is now termed the ‘proteome’ (the protein complement of a genome (Wasinger et al, 1995)) is daunting. Fortunately, the birth of ‘proteomics’, an umbrella term encompassing the many tools available to investigate proteins expressed within cells, fluids, tissues or organisms, has made this task more manageable. These proteomic methods have the power to display and quantify the functional expression of genes, enabling the measurement of disease-associated or phenotypic changes in proteins. Proteomic studies thus have the potential to provide important insights into our understanding of psychiatric, neurodegenerative and neurological diseases. For example, by identifying alterations in protein expression in post-mortem brain they can provide new insights into the cellular mechanism underlying diseases such as schizophrenia. Likewise, by characterising disease-associated protein profiles in sera they may be able to identify and quantify proteins that serve as diagnostic or prognostic markers. Furthermore, proteomic investigation of the effects of pharmaceutical agents in vitro may help us to identify new therapeutic pathways. In this context, it is of interest to discuss how exactly these ‘proteomic’ techniques might be relevant to a psychiatric disease, for example, schizophrenia. Schizophrenia, with its early developmental and later degenerative/atrophic components, is a particularly complex disorder. We know that multiple, largely unidentified genetic (Weinberger et al, 2001) and environmental (Cannon et al, 2003) risk factors interact to lead to disease and disease progression (Thompson et al, 2001). However, the underlying functional changes at the cellular level remain unknown. This is where the strength of a proteomics approach lies, allowing one to identify, quantify and compare the levels of thousands of proteins. The main methods encompassed within this term can be broadly described as those using two-dimensional gel electrophoresis and those using non-gel-based methods to separate and identify proteins in a complex mixture, such as a whole cell or tissue lysate.
Online tuning of fuzzy inference systems using dynamic fuzzy Q-learning

This paper presents a dynamic fuzzy Q-learning (DFQL) method that is capable of tuning fuzzy inference systems (FIS) online. A novel online self-organizing learning algorithm is developed so that structure and parameters identification are accomplished automatically and simultaneously based only on Q-learning. Self-organizing fuzzy inference is introduced to calculate actions and Q-functions so as to enable us to deal with continuous-valued states and actions. Fuzzy rules provide a natural mean of incorporating the bias components for rapid reinforcement learning. Experimental results and comparative studies with the fuzzy Q-learning (FQL) and continuous-action Q-learning in the wall-following task of mobile robots demonstrate that the proposed DFQL method is superior.
Preliminary Draft : Not for citation or circulation Sources of Growth and Productivity in Bangladesh

GDP growth in independent Bangladesh has been on an increasing path and has been its main instrument for poverty reduction. The pace of poverty reduction was most pronounced during the 1990s—with the poverty rate falling from 59 percent to 50 percent—when per-capita GDP growth accelerated to an annual average of 3 percent per annum, the highest post-independence level. Growth has benefited from remarkable macroeconomic stability, sharp declines in the population growth rate, reasonable levels of savings and investment rates, and the low initial income level. Growth has been remarkably stable and Bangladesh is among a handful of countries to have avoided even a single year of negative per-capita growth since the early 1990s—remarkable feat for an economy persistently hit hard by weather related shocks. Even so, Bangladesh’s growth performance falls well short of that of China, the East Asian tigers, and the neighboring India and Sri Lanka. Understanding why, as this paper attempts to, helps identify policy areas with the highest growth potential. The paper shows that productivity growth has been the main driver of growth. It also shows that the most potential for productivity and GDP growth pay-off for Bangladesh lies in policy and institutional improvements that seek to: improve the quality of economic governance; lower regulatory and administrative burdens on businesses; enhance global integration; accelerate human and infrastructure development; improve the quality of financial intermediation; and maintain macroeconomic stability. Even then, financing of the needed increases in the investment levels will be a challenge and will require fiscal prudence and substantial donor support.
Separate Proliferation Kinetics of Fibroblast Growth Factor-Responsive and Epidermal Growth Factor-Responsive Neural Stem Cells within the Embryonic Forebrain Germinal Zone

The embryonic forebrain germinal zone contains two separate and additive populations of epidermal growth factor (EGF)- and fibroblast growth factor (FGF)-responsive stem cells that both exhibit self-renewal and multipotentiality. Although cumulative S phase labeling studies have investigated the proliferation kinetics of the overall population of precursor cells within the forebrain germinal zone through brain development, little is known about when and how (symmetrically or asymmetrically) the small subpopulations of stem cells are proliferating in vivo. This has been determined by injecting timed-pregnant mice with high doses of tritiated thymidine (3H-thy) to kill any stem cells proliferating within the striatal germinal zone in vivoand then by assaying for neurosphere formation in vitro. Injections of 0.8 mCi of 3H-thy given every 2 hr for 12 hr to timed-pregnant mice at E11, E14, and E17 resulted in significant depletions in the number of neurospheres generated by FGF-responsive stem cells at E11 and by EGF-responsive and FGF-responsive stem cells at E14 and E17. With increasing embryonic age, the depletions observed in the number of neurospheres generated in vitro in response to FGF2 after exposure to 3H-thy in vivo decreased, suggesting there is an increase in the length of the cell cycle of FGF-responsive neural stem cells through embryonic development. The results suggest that the FGF-responsive stem cell population expands between E11 and E14 by dividing symmetrically, but switches to primarily asymmetric division between E14 and E17. The EGF-responsive stem cells arise after E11, and their population expands through symmetric divisions and through asymmetric divisions of FGF-responsive stem cells.
Mammalian phospholipid homeostasis: evidence that membrane curvature elastic stress drives homeoviscous adaptation in vivo

Several theories of phospholipid homeostasis have postulated that cells regulate the molecular composition of their bilayer membranes, such that a common biophysical membrane parameter is under homeostatic control. Two commonly cited theories are the intrinsic curvature hypothesis, which states that cells control membrane curvature elastic stress, and the theory of homeoviscous adaptation, which postulates cells control acyl chain packing order (membrane order). In this paper, we present evidence from data-driven modelling studies that these two theories correlate in vivo. We estimate the curvature elastic stress of mammalian cells to be 4–7 × 10−12 N, a value high enough to suggest that in mammalian cells the preservation of membrane order arises through a mechanism where membrane curvature elastic stress is controlled. These results emerge from analysing the molecular contribution of individual phospholipids to both membrane order and curvature elastic stress in nearly 500 cellular compositionally diverse lipidomes. Our model suggests that the de novo synthesis of lipids is the dominant mechanism by which cells control curvature elastic stress and hence membrane order in vivo. These results also suggest that cells can increase membrane curvature elastic stress disproportionately to membrane order by incorporating polyunsaturated fatty acids into lipids.
Comprehensive Protein Interactome Analysis of a Key RNA Helicase: Detection of Novel Stress Granule Proteins

DDX6 (p54/RCK) is a human RNA helicase with central roles in mRNA decay and translation repression. To help our understanding of how DDX6 performs these multiple functions, we conducted the first unbiased, large-scale study to map the DDX6-centric protein-protein interactome using immunoprecipitation and mass spectrometry. Using DDX6 as bait, we identify a high-confidence and high-quality set of protein interaction partners which are enriched for functions in RNA metabolism and ribosomal proteins. The screen is highly specific, maximizing the number of true positives, as demonstrated by the validation of 81% (47/58) of the RNA-independent interactors through known functions and interactions. Importantly, we minimize the number of indirect interaction partners through use of a nuclease-based digestion to eliminate RNA. We describe eleven new interactors, including proteins involved in splicing which is an as-yet unknown role for DDX6. We validated and characterized in more detail the interaction of DDX6 with Nuclear fragile X mental retardation-interacting protein 2 (NUFIP2) and with two previously uncharacterized proteins, FAM195A and FAM195B (here referred to as granulin-1 and granulin-2, or GRAN1 and GRAN2). We show that NUFIP2, GRAN1, and GRAN2 are not P-body components, but re-localize to stress granules upon exposure to stress, suggesting a function in translation repression in the cellular stress response. Using a complementary analysis that resolved DDX6’s multiple complex memberships, we further validated these interaction partners and the presence of splicing factors. As DDX6 also interacts with the E3 SUMO ligase TIF1β, we tested for and observed a significant enrichment of sumoylation amongst DDX6’s interaction partners. Our results represent the most comprehensive screen for direct interaction partners of a key regulator of RNA life cycle and localization, highlighting new stress granule components and possible DDX6 functions—many of which are likely conserved across eukaryotes.
A 868MHz CMOS RF-DC power converter with −17dBm input power sensitivity and efficiency higher than 40% over 14dB input power range

In this paper we present a novel CMOS RF-DC converter circuit, operating at 868MHz, for RFID and remote powering applications. The novel reconfigurable architecture of the converter allows the circuit to operate over a very wide input power range with very high efficiency compared with previous art works. Prototypes realized in STM 0. 130μm CMOS technology provide a regulated output voltage ~2V with a -17dBm input power sensitivity. The circuit efficiency, higher than 40% over a 14dB input power range, peaks at 60%.
A Theoretical Formula for Predicting the Instantaneous Folding Force of the First Fold in a Single Cell Hexagonal Honeycomb under Axial Loading

This article calculates a theoretical formula to predict the instantaneous folding force of the first fold creation in a single cell hexagonal honeycomb under axial loading. For this purpose, the sum of dissipated energy rate under bending around horizontal and inclined hinge lines and that under extensional deformations was equated to the work rate of the external force on the column. The final formula reasonably predicts the instantaneous folding force of the first fold of the thin-walled hexagonal columns during the folding progress. Finally, according to the calculated theoretical relation, the instantaneous folding force of the hexagonal column versus the axial displacement was sketched, and the comparison to the experimental results showed a good correlation.