Miracle-dz/UniFAR-FTUs huggingface dataset:
A Scheduler Support Unit for Reactive Microprocessors

Efficient scheduling mechanisms are essential for implementing real-time operating systems on embedded microprocessors. Reactive processors provide mechanisms and an instruction set architecture more suitable for dealing with external signals than it is the case with traditional interrupts. By extending the reactive framework further we demonstrate simple and efficient hardware-implemented scheduling of tasks with static priorities. The scheduler support unit is added to the reactive microprocessor core. The real-time scheduler shows substantial improvement of performance over the conventional approach of using prioritized interrupts
Automatically Extracting High-Quality Negative Examples for Answer Selection in Question Answering

We propose a heuristic called "one answer per document" for automatically extracting high-quality negative examples for answer selection in question answering. Starting with a collection of question-answer pairs from the popular TrecQA dataset, we identify the original documents from which the answers were drawn. Sentences from these source documents that contain query terms (aside from the answers) are selected as negative examples. Training on the original data plus these negative examples yields improvements in effectiveness by a margin that is comparable to successive recent publications on this dataset. Our technique is completely unsupervised, which means that the gains come essentially for free. We confirm that the improvements can be directly attributed to our heuristic, as other approaches to extracting comparable amounts of training data are not effective. Beyond the empirical validation of this heuristic, we also share our improved TrecQA dataset with the community to support further work in answer selection.
Escherichia coli Fails to Efficiently Maintain the Activity of an Important Flavin Monooxygenase in Recombinant Overexpression

This paper describes the measurement and analysis of in vivo activity and stability of cyclohexanone monooxygenase from Acinetobacter sp. NCIMB 9871 (CHMO), a model Baeyer–Villiger monooxygenase, in the recombinant host Escherichia coli. This enzyme was often described as poorly stable in vitro, and has recently been found to deactivate rapidly in the absence of its essential cofactors and antioxidants. Its stability in vivo was scarcely studied, so far. Under conditions common for the overexpression of CHMO we investigated the ability of the host to support these properties using metabolomics. Our results showed that E. coli failed to provide the intracellular levels of cofactors required to functionally stabilize the enzyme, although the biocatalyst was produced in high concentration, and was invariably detected after protein synthesis had stopped. We thus infer that biotechnological applications of CHMO with this host relied on a residual activity of approximately 5-10%. Other microorganisms might offer a more efficient solution for recombinant production of CHMO and related enzymes.
The Impact of Statistical Leakage Models on Design Yield Estimation

Device mismatch and process variation models play a key role in determining the functionality and yield of sub-100nm design. Average characteristics are often of interest, such as the average leakage current or the average read delay. However, detecting rare functional fails is critical for memory design and designers often seek techniques that enable accurately modeling such events. Extremely leaky devices can inflict functionality fails. The plurality of leaky devices on a bitline increase the dimensionality of the yield estimation problem. Simplified models are possible by adopting approximations to the underlying sum of lognormals. The implications of such approximations on tail probabilities may in turn bias the yield estimate. We review different closed form approximations and compare against the CDF matching method, which is shown to be most effective method for accurate statistical leakage modeling.
Konrad-zuse-zentrum F ¨ Ur Informationstechnik Berlin Models for Railway Track Allocation Models for Railway Track Allocation *

The optimal track allocation problem (OPTRA) is to find, in a given railway network, a conflict free set of train routes of maximum value. We study two types of integer programming formulations for this problem: a standard formulation that models block conflicts in terms of packing constraints, and a novel formulation of the 'extended' type that is based on additional 'configuration' variables. The packing constraints in the standard formulation stem from an interval graph and can therefore be separated in polynomial time. It follows that the LP-relaxation of a strong version of this model, including all clique inequalities from block conflicts, can be solved in polynomial time. We prove that the LP-relaxation of the extended formulation can also be solved in polynomial time, and that it produces the same LP-bound. Albeit the two formulations are in this sense equivalent, the extended formulation has advantages from a computational point of view. It features a constant number of rows and is amenable to standard column generation techniques. Results of an empirical model comparison on mesoscopic data for the Hanover-Fulda-Kassel region of the German long distance railway network involving up to 570 trains are reported.
Physicochemical Properties and Cellular Responses of Strontium-Doped Gypsum Biomaterials

This paper describes some physical, structural, and biological properties of gypsum bioceramics doped with various amounts of strontium ions (0.19–2.23 wt%) and compares these properties with those of a pure gypsum as control. Strontium-doped gypsum (gypsum:Sr) was obtained by mixing calcium sulfate hemihydrate powder and solutions of strontium nitrate followed by washing the specimens with distilled water to remove residual salts. Gypsum was the only phase found in the composition of both pure and gypsum:Sr, meanwhile a shift into lower diffraction angles was observed in the X-ray diffraction patterns of doped specimens. Microstructure of all gypsum specimens consisted of many rod-like small crystals entangled to each other with more elongation and higher thickness in the case of gypsum:Sr. The Sr-doped sample exhibited higher compressive strength and lower solubility than pure gypsum. A continuous release of strontium ions was observed from the gypsum:Sr during soaking it in simulated body fluid for 14 days. Compared to pure gypsum, the osteoblasts cultured on strontium-doped samples showed better proliferation rate and higher alkaline phosphatase activity, depending on Sr concentration. These observations can predict better in vivo behavior of strontium-doped gypsum compared to pure one.
Association of soluble human leukocyte antigen-G with acute tubular necrosis in kidney transplant recipients.

BACKGROUND Human leukocyte antigen (HLA)-G is a nonclassical HLA class I molecule that displays strong immune-inhibitory properties and has been associated with allograft acceptance. However, there are conflicting data on the correlation of soluble HLA-G (sHLA-G) and acute rejection and no data on the correlation with acute tubular necrosis in kidney transplantation. OBJECTIVE To evaluate the association of sHLA-G level in early post-transplant period and allograft rejection/ and acute tubular necrosis (ATN) in kidney transplant recipients. METHODS The sera procured before transplantation and serially on day 3 and day 7 after transplantation from 76 kidney transplant recipients were analyzed for the level of sHLA-G by enzyme-linked immunosorbent assay. RESULTS The levels of sHLA-G from three serial sera did not differ between patients with acute rejection and patients without rejection. However, the sHLA-G levels on day 3 post-transplant and day 7 post-transplant in patients with ATN were significantly higher than that in patients without ATN (16.3 vs 9.85 U/ml, p = 0.018, for day 3 post-transplant and 12.47 vs 5.42 U/ml, p = 0.044, for day 7 post-transplant). In addition, the ROC analysis of sHLA-G for identifying patients with ATN showed that the area under curve was 0.67 (95% confidence interval 0.54-0.80). CONCLUSIONS There was no significant difference for sHLA-G levels between patients with acute rejection and without rejection. Interestingly, high levels of sHLA-G in day 3 and day 7 after transplantation were associated with acute tubular necrosis. Our findings raise the question whether the increased levels of sHLA-G in patients with acute tubular necrosis after transplantation might be a result of ischemia and reperfusion injury.
IgG Anti-GT1a antibodies which do not cross react with GQ1b ganglioside in a pharyngeal-cervical-brachial variant of Guillain-Barré syndrome

IgG anti-GT1a antibody which cross reacts with GQ1b ganglioside is associated with ophthalmoplegia in Guillain-Barre syndrome and in Fisher’s syndrome, a variant of Guillain-Barre syndrome.1 Pharyngeal-cervical-brachial weakness is another regional variant of Guillain-Barre syndrome originally described by Ropper.2 Its symptoms resemble those of botulism and diphtheria and are characterised by marked oropharyngeal, neck, and shoulder weakness with areflexia only in the arms. We report on a patient with this variant who had high titres of serum IgG anti-GT1a antibody which did not cross react with GQ1b. Thin layer chromatography with immunostaining. Thin layer chromatography plates stained with (A) orcinol/sulphuric acid for hexose; (B) IgG from our patient, subsequently stained by peroxidase conjugated antihuman IgG antibodies; (C) IgG from a patient with Bickerstaff’s brain stem encephalitis. Lane 1: bovine brain ganglioside mixtures. Lane 2: the GD1a and GT1a fraction separated from bovine brain ganglioside mixtures by Q-sepharose column chromatography. Lane 3: fraction enriched with GT1a and GQ1b. The plates were developed with C-M-0.2% calcium chloride in water (5:4:1 by volume). A 55 year-old woman was admitted due to sudden onset ptosis, trouble with swallowing, and nausea and vomiting. One week before admission she had had an upper respiratory infection with diarrhoea which lasted for several days. On admission, …
THREE LECTURES ON HYPERGEOMETRIC FUNCTIONS

In this course we will study multivariate hypergeometric functions in the sense of Gel'fand, Kapranov, and Zelevinsky (GKZ systems). These functions generalize the classical hypergeometric functions of Gauss, Horn, Appell, and Lauricella. We will emphasize the alge- braic methods of Saito, Sturmfels, and Takayama to construct hypergeometric series and the connection with deformation techniques in commutative algebra. We end with a brief discussion of the classiflcation problem for rational hypergeometric functions. Resumen. En este curso se estudiaran las funciones hipergeometricas multivaluadas en el sen- tido de Gel'fand, Kapranov, y Zelevinsky (sistemas GKZ). Estas funciones generalizan las funciones hipergeometricas de Gauss, Horn, Appell, y Lauricella. Se exploraran los metodos al- gebraicos de Saito, Sturmfels, y Takayama para construir series hipergeometricas y la aplicacion de tecnicas de algebra conmutativa. El curso concluye con una breve discusion del problema de caracterizacion de funciones hipergeometricas racionales.
Behavioral and Electrophysiological Effects of Intracranially Applied Neuropeptides with Special Attention to DC Slow Potential Changes a

lntracranial administration of certain neuropeptides can induce massive changes in EEG activity and the DC slow potential, referred to as “spreading depression. ” Spreading depression, which is difficult to recognize in EEG recordings, has various behavioral consequences. This report summarizes studies dealing with the elicitation of “spreading depression” by neuropeptides and the concomitant behavioral changes commonly (mistakenly) attributed to physiological effects of intracranially injected neuropeptides. The application of various neuropeptides into the brain can elicit behaviors such as “wet-dog’’ shaking, grooming, circling, changes in locomotor activity, immobility, analgesia, and barrel rotations. Similar behaviors accompany spreading depression (SD) triggered by electrical, mechanical, or chemical stimulation in certain brain regions. Therefore, we hypothesized that certain behavioral changes that follow the intracranial administration of some neuropeptides are a direct consequence of SD. Our first experiments demonstrated that the injection of certain neuropeptides into the brain can induce SD in the anesthetized animal. The application of nanogram amounts of vasopressin and microgram amounts of ACTHI-,,. Leuand Metenkephalin, and the Met-enkephalin analogue [~-Ala-2]Met-enkephalinamide (DAME) into the cortex and/or hippocampus of rats elicited SD.1-3 In the case of the enkephalins and DAME, their SDand seizure-inducing activity was blocked or partly antagonized by the opiate antagonist naloxone. The finding that some neuropeptides are able to induce SD in the anesthetized rat led us to record EEG, DC slow potentials, and behavioral responses concurrently after hippocampal injection of ACTHI-,, and DAME in the freely moving animaL4 We wished to determine whether certain behavioral effects of intracranial injection of neuropeptides (e.g., wet-dog shaking, hyperactivity or immobility, and analgesia for DAME; grooming for ACTHI-,,) are the behavioral expression of SD rather than peptide-specific responses.
Topological robot localization by training a vision-based transition detector

This paper presents a mobile robot localizer that detects topological transitions using a color vision-based classification system. After a two-step training process, the localization system is shown to achieve sufficient reliability to track the position of a mobile robot across two floors of an office building using purely discrete (non-probabilistic) update. Experimental results are based on an off-the-shelf electric wheelchair fitted with a parabolic color camera.
Implicit linguistic structure in connected speech

This paper sketches a model of early emergence of basic linguistic structure using general-purpose similarity measures, without a priori linguistic knowledge, to structure natural speech signals. The model attempts to mimic a first language learning situation. Crude auditory representations of the acoustic signal are continuously stored in memory and processed to detect similarities between portions of the representation patterns. The similarity measures are purely auditory and allow only for moderate time warping and frequency shifts, picking up any best matches among the stored patterns and between these and incoming speech. An example of the model performance is presented.
Imaging Diagnosis of Splanchnic Venous Thrombosis

Splanchnic vein thrombosis (SVT) is a broad term that includes Budd-Chiari syndrome and occlusion of veins that constitute the portal venous system. Due to the common risk factors involved in the pathogenesis of these clinically distinct disorders, concurrent involvement of two different regions is quite common. In acute and subacute SVT, the symptoms may overlap with a variety of other abdominal emergencies while in chronic SVT, the extent of portal hypertension and its attendant complications determine the clinical course. As a result, clinical diagnosis is often difficult and is frequently reliant on imaging. Tremendous improvements in vascular imaging in recent years have ensured that this once rare entity is being increasingly detected. Treatment of acute SVT requires immediate anticoagulation. Transcatheter thrombolysis or transjugular intrahepatic portosystemic shunt is used in the event of clinical deterioration. In cases with peritonitis, immediate laparotomy and bowel resection may be required for irreversible bowel ischemia. In chronic SVT, the underlying cause should be identified and treated. The imaging manifestations of the clinical syndromes resulting from SVT are comprehensively discussed here along with a brief review of the relevant clinical features and therapeutic approach.
Dynamic Analysis of DC-DC Boost Converter Based on Its Nonlinear Characteristics

Conventional small-signal models obtained by state-space averaging method can be conveniently used in dynamic analysis of DC-DC switching converters. However, validity of these models is often influenced due to nonlinear characteristics of switching power converters. In this paper, a sampled-data model is used to analyze the nonlinear characteristics of boost converter operating in continuous mode. Based on its result, the cause which leads to the loss of validity of the small-signal averaged model is found and a method to correct the small-signal model is proposed
Effect of NASA light-emitting diode irradiation on molecular changes for wound healing in diabetic mice.

OBJECTIVE The purpose of this study was to assess the changes in gene expression of near-infrared light therapy in a model of impaired wound healing. BACKGROUND DATA Light-Emitting Diodes (LED), originally developed for NASA plant growth experiments in space, show promise for delivering light deep into tissues of the body to promote wound healing and human tissue growth. In this paper we present the effects of LED treatment on wounds in a genetically diabetic mouse model. MATERIALS AND METHODS Polyvinyl acetal (PVA) sponges were subcutaneously implanted in the dorsum of BKS.Cg-m +/+ Lepr(db) mice. LED treatments were given once daily, and at the sacrifice day, the sponges, incision line and skin over the sponges were harvested and used for RNA extraction. The RNA was subsequently analyzed by cDNA array. RESULTS Our studies have revealed certain tissue regenerating genes that were significantly upregulated upon LED treatment when compared to the untreated sample. Integrins, laminin, gap junction proteins, and kinesin superfamily motor proteins are some of the genes involved during regeneration process. These are some of the genes that were identified upon gene array experiments with RNA isolated from sponges from the wound site in mouse with LED treatment. CONCLUSION We believe that the use of NASA light-emitting diodes (LED) for light therapy will greatly enhance the natural wound healing process, and more quickly return the patient to a preinjury/illness level of activity. This work is supported and managed through the Defense Advanced Research Projects Agency (DARPA) and NASA Marshall Space Flight Center-SBIR Program.
Entity-Linking via Graph-Distance Minimization

Entity-linking is a natural-language-processing task that consists in identifying the entities mentioned in a piece of text, linking each to an appropriate item in some knowledge base; when the knowledge base is Wikipedia, the problem comes to be known as wikification (in this case, items are wikipedia articles). One instance of entity-linking can be formalized as an optimization problem on the underlying concept graph, where the quantity to be optimized is the average distance between chosen items. Inspired by this application, we define a new graph problem which is a natural variant of the Maximum Capacity Representative Set. We prove that our problem is NP-hard for general graphs; nonetheless, under some restrictive assumptions, it turns out to be solvable in linear time. For the general case, we propose two heuristics: one tries to enforce the above assumptions and another one is based on the notion of hitting distance; we show experimentally how these approaches perform with respect to some baselines on a real-world dataset.
Self-association of the Spindle Pole Body-related Intermediate Filament Protein Fin1p and Its Phosphorylation-dependent Interaction with 14-3-3 Proteins in Yeast*

The Fin1 protein of the yeastSaccharomyces cerevisiae forms filaments between the spindle pole bodies of dividing cells. In the two-hybrid system it binds to 14-3-3 proteins, which are highly conserved proteins involved in many cellular processes and which are capable of binding to more than 120 different proteins. Here, we describe the interaction of the Fin1 protein with the 14-3-3 proteins Bmh1p and Bmh2p in more detail. Purified Fin1p interacts with recombinant yeast 14-3-3 proteins. This interaction is strongly reduced after dephosphorylation of Fin1p. Surface plasmon resonance analysis showed that Fin1p has a higher affinity for Bmh2p than for Bmh1p (K D 289versus 585 nm). Sequences in both the central and C-terminal part of Fin1p are required for the interaction with Bmh2p in the two-hybrid system. In yeast strains lacking 14-3-3 proteins Fin1 filament formation was observed, indicating that the 14-3-3 proteins are not required for this process. Fin1 also interacts with itself in the two-hybrid system. For this interaction sequences at the C terminus, containing one of two putative coiled-coil regions, are sufficient. Fin1p-Fin1p interactions were demonstrated in vivo by fluorescent resonance energy transfer between cyan fluorescent protein-labeled Fin1p and yellow fluorescent protein-labeled Fin1p.
Using rules to enhance evolution of knowledge mapping: Application on Healthcare

Preserve knowledge, retain knowledge, these are the objectives of a scalable enterprise. Knowledge mapping is graphical techniques which allows of preserving and visualizing the patrimony strategic and trades of the domains of knowledge acquired over the years. The approach presented in this paper draws, firstly, on the exploitation of different data sources for improving the process of acquisition of explicit knowledge on an organization. In this sense, our contribution is to produce, from one hand inductive Boolean rules that will feed knowledge base CASI, and from other hand, refinement of Boolean model of the knowledge mapping already achieved by the MASKII method (Critical Knowledge Mapping).
Segmentation of offline handwritten Arabic text

Arabic script is cursive in both printed and handwritten forms. This intrinsic nature of cursiveness renders the segmentation task challenging. An Arabic word generally consists of multiple parts known as Parts of Arabic Words (PAWs) or simply sub-words. Sub-words share the same vertical space quite frequently which makes vertical projection segmentation technique inefficient. Several Arabic letters have annexed parts (diacritics) which are located above or below the main parts of the character. The relative positions of the annexed parts and main parts vary a lot in handwritten text. In this paper the task of segmenting offline handwritten Arabic text up to character level is taken up. Firstly, graph-theoretic modeling is utilized to extract connected components of word image. These components are subjected to a thorough analysis to facilitate the segmentation of input image into sub-words. In the sequel diacritics are removed. Then, large number of candidate segmentation points is identified based on two strategies that utilize stroke thickness as a heuristic. Final segmentation points are obtained using a set of rules on the candidate segmentation points. Finally, each sub-word is segmented and diacritics are brought back to their respective segments taking into account the issue of diacritics displacement. Experimentation is conducted on a set of handwritten images of Arabic text drawn from IFN/ENIT dataset. The results obtained are encouraging.