Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of efficacy of novel modified chitosan sponge dressing in a lethal arterial injury model in swine

BACKGROUND: Chitosan is a functional biopolymer that has been widely used as a hemostat. Recently, its efficacy has been questioned due to clinical failures as a result of poor adhesiveness. The purpose of this study was to compare, in a severe groin injury model in swine, the hemostatic properties of an unmodified standard chitosan sponge with standard gauze dressing and a novel hydrophobically modified (hm) chitosan sponge. Previous studies have demonstrated that hm-chitosan provides greatly enhanced cellular adhesion and hemostatic effect via noncovalent insertion of hydrophobic pendant groups into cell membranes. METHODS: Twenty-four Yorkshire swine were randomized to receive hm-chitosan (n = 8), unmodified chitosan (n = 8), or standard Accu-Sorb gauze dressing (n = 8) for hemostatic control. A complex groin injury involving arterial puncture (4.4-mm punch) of the femoral artery was made after splenectomy. After 30 seconds of uncontrolled hemorrhage, the randomized dressing was applied and compression was held for 3 minutes. Fluid resuscitation was initiated to achieve and maintain the baseline mean arterial pressure and the wound was inspected for bleeding. Failure of hemostasis was defined as pooling of blood outside the wound. Animals were then monitored for 180 minutes and surviving animals were killed. RESULTS: Blood loss before treatment was similar between groups (p < 0.1). Compared with the hm-chitosan sponge group, which had no failures, the unmodified chitosan sponge group and the standard gauze group each had eight failures over the 180-minute observation period. For the unmodified chitosan sponge failures, six of which provided initial hemostasis, secondary rebleeding was observed 44 minutes ± 28 minutes after application. Standard gauze provided no initial hemostasis after the 3-minute compression interval. CONCLUSIONS: Hm-chitosan is superior to unmodified chitosan sponges (p < 0.001) or standard gauze for controlling bleeding from a lethal arterial injury. The hm-chitosan technology may provide an advantage over native chitosan-based dressings for control of active hemorrhage.
A randomized double-blind placebo-controlled clinical study on the effects of gabapentin premedication on hemodynamic stability during laparoscopic cholecystectomy

Background: Carbon dioxide pneumoperitoneum for laparoscopic surgery increases arterial pressures, heart rate, and systemic vascular resistance. In this randomized double-blind placebo-controlled clinical study, we investigated the efficacy of gabapentin premedication to provide perioperative hemodynamic stability in patients undergoing laparoscopic cholecystectomy. Materials and Methods: Sixty patients, of either sex (18–65 years of age) undergoing elective laparoscopic cholecystectomy were randomly allocated to two groups of 30 patients each. Patients of group G received oral gabapentin 900 mg 2 h before induction of anesthesia, while patients in group P received placebo at the same time. Results: Mean arterial pressure in patients of group G were significantly lower (P < 0.05) after tracheal intubation and pneumoperitoneum and remained lower, as compared to group P, throughout the pneumoperitoneum. Similarly, heart rate in group G was significantly lower (P < 0.05) after tracheal intubation and pneumoperitoneum and remained lower, in comparison to group P, throughout the peumoperitoneum. Intravenous labetalol was required, to control intraoperative hypertension, in 33.3% (10 out of 30) patients in group P. There was no significant difference in the incidence of adverse effects between the two groups. Conclusion: Gabapentin premedication provided perioperative hemodynamic stability during laparoscopic surgery.
Hierarchical Statistical Shape Analysis and Prediction of Sub-Cortical Brain Structures

In this paper, we present the application of two multivariate statistical techniques to investigate how different structures within the brain vary statistically relative to each other. The first of these techniques is canonical correlation analysis which extracts and quantifies correlated behaviour between two sets of vector variables. The second technique is partial least squares regression which determines the best factors within a first set of vector variables for predicting a vector variable from a second set. We describe how these techniques can be used to quantify and predict correlated behaviour in sub-cortical structures within the brain using 3D MR images.
Security Issues and Attacks in Wireless Sensor Network

Wireless sensor network is one of the most growing technology for sensing and performing the different tasks. Such networks are beneficial in many fields, such as emergencies, health monitoring, environmental control, military, industries and these networks prone to malicious users' and physical attacks due to radio range of network, un-trusted transmission, unattended nature and get access easily. Security is a fundamental requirement for these networks. In this paper, our center of attention is on physical attacks and issues in wireless sensor networks. Through this review, easily identify the purpose and capabilities of the attackers. Further, we discuss well-known approaches of security detection against physical attacks.
Parallel Search for Boolean Optimization

The predominance of multicore processors has increased the inter- est in developing parallel Boolean Satisfiability (SAT) solvers. As a result, more parallel SAT solvers are emerging. Even though parallel approaches are known to boost performance, parallel approaches developed for Boolean optimization are scarce. This paper proposes parallel search algorithms for Boolean optimiza- tion and introduces a new parallel solver for Boolean optimization problem in- stances. Using two threads, an unsatisfiability-based algorithm is used to search on the lower bound value of the objective function, while at the same time a linear search is performed on the upper bound value of the objective function. Searching in both directions and exchanging learned clauses between these two orthogonal approaches makes the search more efficient. This idea is further extended for a larger number of threads by dividing the search space considering different local upper values of the objective function. The parallel search on different local up- per values leads to constant updates on the lower and upper bound values, which result in reducing the search space. Moreover, different search strategies are per- formed on the upper bound value, increasing the diversification of the search.
The relationship between transplacental O2 diffusion and placental expression of PlGF, VEGF and their receptors in a placental insufficiency model of fetal growth restriction

Placental growth factor (PlGF) and vascular endothelial growth factor (VEGF) are involved in placental angiogenesis through interactions with the VEGFR‐1 and VEGFR‐2 receptors. The placenta of pregnancies whose outcome is fetal growth restriction (FGR) are characterized by abnormal angiogenic development, classically associated with hypoxia. The present study evaluated the near‐term expression of this growth factor family in an ovine model of placental insufficiency–FGR, in relationship to uteroplacental oxygenation. Compared to controls, FGR pregnancies demonstrated a 37 % increase in uterine blood flow (FGR vs. control, 610.86 ± 48.48 vs. 443.17 ± 37.39 ml min−1 (kg fetus)−1; P < 0.04), which was associated with an increased maternal uterine venous PO2 (58.13 ± 1.00 vs. 52.89 ± 1.26 mmHg; P < 0.02), increased umbilical artery systolic/diastolic ratio (3.90 ± 0.33 vs. 2.12 ± 0.26, P < 0.05), and fetal hypoxia (arterial PO2; 12.79 ± 0.97 vs. 18.65 ± 1.6 mmHg, P < 0.005). Maternal caruncle PlGF mRNA was increased in FGR (P < 0.02), while fetal cotyledon VEGF mRNA was reduced (P < 0.02). VEGFR‐1 mRNA was also reduced in FGR fetal cotyledon (P < 0.001) but was not altered in caruncle tissue. Immunoblot analysis of PlGF and VEGF demonstrated single bands at 19 000 and 18 600 Mr, respectively. Caruncle PlGF concentration was increased (P < 0.04), while cotyledon VEGF was decreased (P < 0.05) in FGR placentae. The data establish that uterine blood flow is not reduced in relationship to metabolic demands in this FGR model and that the transplacental PO2 gradient is increased, maintaining umbilical oxygen uptake per unit of tissue. Furthermore, these data suggest that an increased transplacental gradient of oxygen generates changes in angiogenic growth factors, which may underline the pathophysiology of the post‐placental hypoxic FGR.
Rollback-Recovery for Middleboxes

Network middleboxes must offer high availability, with automatic failover when a device fails. Achieving high availability is challenging because failover must correctly restore lost state (e.g., activity logs, port mappings) but must do so quickly (e.g., in less than typical transport timeout values to minimize disruption to applications) and with little overhead to failure-free operation (e.g., additional per-packet latencies of 10-100s of us). No existing middlebox design provides failover that is correct, fast to recover, and imposes little increased latency on failure-free operations. We present a new design for fault-tolerance in middleboxes that achieves these three goals. Our system, FTMB (for Fault-Tolerant MiddleBox), adopts the classical approach of "rollback recovery" in which a system uses information logged during normal operation to correctly reconstruct state after a failure. However, traditional rollback recovery cannot maintain high throughput given the frequent output rate of middleboxes. Hence, we design a novel solution to record middlebox state which relies on two mechanisms: (1) 'ordered logging', which provides lightweight logging of the information needed after recovery, and (2) a `parallel release' algorithm which, when coupled with ordered logging, ensures that recovery is always correct. We implement ordered logging and parallel release in Click and show that for our test applications our design adds only 30$\mu$s of latency to median per packet latencies. Our system introduces moderate throughput overheads (5-30%) and can reconstruct lost state in 40-275ms for practical systems.
Four Fundamental Methodological Problems of Landscape Geography

Abstract Fundamental methodological problems of geography as a science have been identified by Chojnicki (1999) in the following list: goal of research, separate character of research, expected results, and form of scientific explanation. This article presents methodological stand-points taken be landscape geographers towards the above problems, which proved to be as diverse as in the case of the human geography. The article highlights negative consequences of such state of affairs.
Sliding Mode Control for VTOL Aircraft Based on High-Gain Observer

Based on the high-gain observer technique, this paper proposes a sliding mode control strategy for VTOL aircraft. The merit of this control strategy is that this paper gets exponential stability results of VTOL aircraft tracking control system. VTOL aircraft is a typical nonlinear underactuated system, based on the characteristics of this model, after four reversible coordinate transformation, the original mathematical model is transformed into a coordinate standard mode, then design a sliding mode controller. Another challenge for control design is that some states needed in the control schemes are not available. In order to solve this problem, a high-gain observer is utilized. The stability of the closed-loop system is verified via Lyapunov method and separation principle. The simulation results show that this method can solve VTOL aircraft trajectory tracking problem using only output feedback.
Diffusion Models for Information Dissemination Dynamics in Wireless Complex Communication Networks

Information dissemination has become one of the most important services of communication networks. Modeling the diffusion of information through such networks is crucial for our modern information societies. In this work, novel models, segregating between useful and malicious types of information, are introduced, in order to better study Information Dissemination Dynamics (IDD) in wireless complex communication networks, and eventually allow taking into account special network features in IDD. According to the proposed models, and inspired from epidemiology, we investigate the IDD in various complex network types through the use of the Susceptible-Infected (SI) paradigm for useful information dissemination and the Susceptible-Infected-Susceptible (SIS) paradigm for malicious information spreading. We provide analysis and simulation results for both types of diffused information, in order to identify performance and robustness potentials for each dissemination process with respect to the characteristics of the underlying complex networking infrastructures. We demonstrate that the proposed approach can generically characterize IDD in wireless complex networks and reveal salient features of dissemination dynamics in each network type, which could eventually aid in the design of more advanced, robust, and efficient networks and services.
A Mouse Model of Hemorrhagic Transformation by Delayed Tissue Plasminogen Activator Administration After In Situ Thromboembolic Stroke

Background and Purpose— Thrombolytic treatment with tissue plasminogen activator (tPA) improves outcome of patients with stroke who can be treated within 3 hours of symptom onset. However, delayed treatment with tPA leads to increased risk of hemorrhagic transformation and can result in enhanced brain injury. The purpose of this study is to validate a reproducible mouse model of hemorrhagic transformation associated with delayed administration of tPA. Methods— Mice were anesthetized and thrombin was injected into the middle cerebral artery to induce the formation of a clot as described by Orset et al. To induce reperfusion, tPA (10 mg/kg) was intravenously administered 20 minutes or 3 hours after thrombin injection. Results— Thrombin produced a clot in 83.1% of the animals, which caused focal ischemia determined 24 hours after the injection. Different degrees of bleeding were found in the middle cerebral artery occlusion group, including hemorrhagic infarction type 1 (HI-1) in 46.2%, hemorrhagic infarction type 2 (HI-2) in 30.8% and parenchymal hemorrhage type 1 in 23.0%. Administration of tPA 20 minutes after the occlusion produced an effective reperfusion in 62.5% of the animals and reduced both infarct volume and appearance of severe hemorrhage (10% nonhemorrhage, 80% HI-1 and 10% HI-2). However, administration of tPA 3 hours after the occlusion led to effective reperfusion in 47.1% of the animals, did not reduce infarct volume, caused hemorrhagic transformation (25% HI-1, 37.5% HI-2, and 37.5% parenchymal hemorrhage type 1), and increased hemorrhage and brain swelling. Conclusions— We have set up a reproducible mouse model of hemorrhagic transformation associated with delayed administration of tPA similar to that observed in humans.
A comprehensive scheduler for asymmetric multicore systems

Symmetric-ISA (instruction set architecture) asymmetric-performance multicore processors were shown to deliver higher performance per watt and area for applications with diverse architectural requirements, and so it is likely that future multicore processors will combine a few fast cores characterized by complex pipelines, high clock frequency, high area requirements and power consumption, and many slow ones, characterized by simple pipelines, low clock frequency, low area requirements and power consumption. Asymmetric multicore processors (AMP) derive their efficiency from core specialization. Efficiency specialization ensures that fast cores are used for "CPU-intensive" applications, which efficiently utilize these cores' "expensive" features, while slow cores would be used for "memory-intensive" applications, which utilize fast cores inefficiently. TLP (thread-level parallelism) specialization ensures that fast cores are used to accelerate sequential phases of parallel applications, while leaving slow cores for energy-efficient execution of parallel phases. Specialization is effected by an asymmetry-aware thread scheduler, which maps threads to cores in consideration of the properties of both. Previous asymmetry-aware schedulers employed one type of specialization (either efficiency or TLP), but not both. As a result, they were effective only for limited workload scenarios. We propose, implement, and evaluate CAMP, a Comprehensive AMP scheduler, which delivers both efficiency and TLP specialization. Furthermore, we propose a new light-weight technique for discovering which threads utilize fast cores most efficiently. Our evaluation in the OpenSolaris operating system demonstrates that CAMP accomplishes an efficient use of an AMP system for a variety of workloads, while existing asymmetry-aware schedulers were effective only in limited scenarios.
Lecture 3: Lower Bounds for Bandit Algorithms

Note that (2) implies (1) since: if regret is high in expectation over problem instances, then there exists at least one problem instance with high regret. Also, (1) implies (2) if |F| is a constant. This can be seen as follows: suppose we know that for any algorithm we have high regret (say H) with one problem instance in F and low regret with all other instances in F , then, taking a uniform distribution over F , we can say that any algorithm has expected regret at least H/|F|. (So this argument breaks if |F| is large.) If we prove a stronger version of (1) that says that for any algorithm, regret is high for a constant fraction of the problem instances in F , then, considering a uniform distribution over F , this implies (2) regardless of whether |F| is large or not. In this lecture, for proving lower bounds, we consider 0-1 rewards and the following family of problem instances (with fixed to be adjusted in the analysis):
Combining Lexical-Syntactic Information with Machine Learning for Recognizing Textual Entailment

This document contains the description of the experiments carried out by SINAI group. We have developed an approach based on several lexical and syntactic measures integrated by means of different machine learning models. More precisely, we have evaluated three features based on lexical similarity and 11 features based on syntactic tree comparison. In spite of the relatively straightforward approach we have obtained more than 60% for accuracy. Since this is our first participation we think we have reached a good result.
Energetic Natural Gradient Descent

We propose a new class of algorithms for minimizing or maximizing functions of parametric probabilistic models. These new algorithms are natural gradient algorithms that leverage more information than prior methods by using a new metric tensor in place of the commonly used Fisher information matrix. This new metric tensor is derived by computing directions of steepest ascent where the distance between distributions is measured using an approximation of energy distance (as opposed to Kullback-Leibler divergence, which produces the Fisher information matrix), and so we refer to our new ascent direction as the energetic natural gradient.
Nonparametric Item Response Function Estimates with the EM Algorithm

The methods of functional data analysis are used to estimate item response functions (IRFs) nonparametrically. The EM algorithm is used to maximize the penalized marginal likelihood of the data. The penalty controls the smoothness of the estimated IRFs, and is chosen so that, as the penalty is increased, the estimates converge to shapes closely represented by the three-parameter logistic family. The one-dimensional latent trait model is recast as a problem of estimating a space curve or manifold, and, expressed in this way, the model no longer involves any latent constructs, and is invariant with respect to choice of latent variable. Some results from differential geometry are used to develop a data-anchored measure of ability and a new technique for assessing item discriminability. Functional data-analytic techniques are used to explore the functional variation in the estimated IRFs. Applications involving simulated and actual data are included.
Dexamethasone Induces Cell Death in Insulin-Secreting Cells, an Effect Reversed by Exendin-4

Glucocorticoid excess induces hyperglycemia, which may result in diabetes. The present experiments explored whether glucocorticoids trigger apoptosis in insulin-secreting cells. Treatment of mouse β-cells or INS-1 cells with the glucocorticoid dexamethasone (0.1 μmol/l) over 4 days in cell culture increased the number of fractionated nuclei from 2 to 7 and 14%, respectively, an effect that was reversed by the glucocorticoid receptor antagonist RU486 (1 μmol/l). In INS-1 cells, dexamethasone increased the number of transferase-mediated dUTP nick-end labeling–staining positive cells, caspase-3 activity, and poly-(ADP-) ribose polymerase protein cleavage; decreased Bcl-2 transcript and protein abundance; dephosphorylated the proapoptotic protein of the Bcl-2 family (BAD) at serine155; and depolarized mitochondria. Dexamethasone increased PP-2B (calcineurin) activity, an effect abrogated by FK506. FK506 (0.1 μmol/l) and another calcineurin inhibitor, deltamethrin (1 μmol/l), attenuated dexamethasone-induced cell death. The stable glucagon-like peptide 1 analog, exendin-4 (10 nmol/l), inhibited dexamethasone-induced apoptosis in mouse β-cells and INS-1 cells. The protective effect of exendin-4 was mimicked by forskolin (10 μmol/l) but not mimicked by guanine nucleotide exchange factor with the specific agonist 8CPT-Me-cAMP (50 μmol/l). Exendin-4 did not protect against cell death in the presence of cAMP-dependent protein kinase (PKA) inhibition by H89 (10 μmol/l) or KT5720 (5 μmol/l). In conclusion, glucocorticoid-induced apoptosis in insulin-secreting cells is accompanied by a downregulation of Bcl-2, activation of calcineurin with subsequent dephosphorylation of BAD, and mitochondrial depolarization. Exendin-4 protects against glucocorticoid-induced apoptosis, an effect mimicked by forskolin and reversed by PKA inhibitors.
The Exopolysaccharide Alginate Protects Pseudomonas aeruginosa Biofilm Bacteria from IFN-γ-Mediated Macrophage Killing1

The ability of Pseudomonas aeruginosa to form biofilms and cause chronic infections in the lungs of cystic fibrosis patients is well documented. Numerous studies have revealed that P. aeruginosa biofilms are highly refractory to antibiotics. However, dramatically fewer studies have addressed P. aeruginosa biofilm resistance to the host’s immune system. In planktonic, unattached (nonbiofilm) P. aeruginosa, the exopolysaccharide alginate provides protection against a variety of host factors yet the role of alginate in protection of biofilm bacteria is unclear. To address this issue, we tested wild-type strains PAO1, PA14, the mucoid cystic fibrosis isolate, FRD1 (mucA22+), and the respective isogenic mutants which lacked the ability to produce alginate, for their susceptibility to human leukocytes in the presence and absence of IFN-γ. Human leukocytes, in the presence of recombinant human IFN-γ, killed biofilm bacteria lacking alginate after a 4-h challenge at 37°C. Bacterial killing was dependent on the presence of IFN-γ. Killing of the alginate-negative biofilm bacteria was mediated through mononuclear cell phagocytosis since treatment with cytochalasin B, which prevents actin polymerization, inhibited leukocyte-specific bacterial killing. By direct microscopic observation, phagocytosis of alginate-negative biofilm bacteria was significantly increased in the presence of IFN-γ vs all other treatments. Addition of exogenous, purified alginate to the alginate-negative biofilms restored resistance to human leukocyte killing. Our results suggest that although alginate may not play a significant role in bacterial attachment, biofilm development, and formation, it may play an important role in protecting mucoid P. aeruginosa biofilm bacteria from the human immune system.