Miracle-dz/UniFAR-FTUs huggingface dataset:
Amperometric enzyme-based biosensors : refined bioanalytical tools for in vivo biomonitoring

Diabetes Mellitus is a chronic disease characterized by poor glucose regulation. On a long term, diabetes can lead to severe complications such as nephropathies, neuropathies, blindness and cardiovascular disorders. It is currently a leading cause of death, worldwide. With the number of diabetes patients rapidly increasing, the need for a solutions to improve glucose control became crucial. Despite endless evidence that continuous glucose monitoring (CGM) leads to better diabetes management state-of-the art CGM devices are still hampered by poor accuracy and (very) short lifetimes. These devices rely on biosensor measurements that still require frequent calibrations, dependent on painful blood glucose measurements. Therefore, CGM devices far from replacing the burdensome blood glucose monitoring as the method of choice in diabetes management. Here, we describe a wireless implantable microbiosensor based device (iMBD) for CGM. The glucose biosensors of our CGM device are based on needle type electrodes platinum microelectrodes. Microelectrode surfaces were functionalized, first with a permselective and after with an enzymatic hydrogel (Glucose Oxidase). All biosensors were then covered with an hollow dialysis membrane. We assembled and characterized in vitro, various amperometric enzyme-based glucose biosensor designs. Thorough electrochemical evaluation allowed us to select the most suitable one (Pt200/Nafion/GOx/PE) to be incorporated in the wireless CGM device. The performance of the device was evaluated in vivo by its implantation in the subcutaneous tissue of freely moving rats, for 5 days. After, all iMBD were explanted and re-calibrated to assess biofouling effects. Conversion of the in vivo CGM signals into glucose levels was performed by single and multiple point blood calibration. The presented device was able to monitor, wirelessly continuously and in real-time subcutaneous glucose levels in freely moving animals. Additionally the device was able to detect glucose levels manipulated by pharmacological treatments. These changes were well correlated with concurrent changes in blood glucose, suggesting that the proposed approach may represent a viable option for better glucose management. CHAPTER 4
The impact of design debugging on new product development speed : the significance of improvisational and trial-and-error learning

Investigating the antecedents of cycle time reduction is a continuing concern within new product development (NPD) research (Chen et al., 2010; Cankurtaran et al., 2013). A number of researchers have reported the effects of team learning on NPD speed (Dayan and Di Benedetto, 2008; Cankurtaran et al., 2013), while others relate learning to overall team performance (Magni et al., 2013). However, few studies have systematically researched the effects of improvisation and trial-and-error learning on NPD cycle time. The aim of this study is to shine new light on NPD learning and cycle time reduction through an examination of the effects of improvisation and trial-and-error. To that end, this study conceptualizes and tests the settings wherein improvisation and trial-and-error might contribute or hinder NPD cycle time reduction. The authors develop hypothesis to investigate the effects of improvisation and trialand-error learning on NPD cycle time. Based on a review of the literature and in-depth interviews measures are defined to approximate improvisation and trial-and-error using secondary data from over 200 projects with absolute objective measures of cycle time. In addition, 1000s archival records of debugging incidents and engineering changes are used to approximate the impact of improvisation and trial-and-error. To estimate their impact on cycle time a learning curve model is developed (Argote, 2012) which offers an effective way of identifying the conditions that drive cycle time learning and performance (Wiersma, 2007). Based on this model the hypotheses are tested. The findings suggest that improvisation and trial-and-error contribute to cycle time learning in the prototyping and pilot phases only, and that they hinder learning during later stages in the NPD process. These findings contribute to the extant literature by providing an important new organizational learning perspective on NPD speed. The study contributes to practice by relating firms’ improvisation and trial-and-error practices to learning and speed performance.
Martian Gullies: Variety of Settings and Implications for Formation Processes

PROCESSES. J.L. Heldmann , K.S. Edgett, O.B. Toon, and M.T. Mellon, NASA Ames Research Center, MS 245-3 Moffett Field, CA 94035, Jennifer.Heldmann@nasa.gov, Malin Space Science Systems, San Diego, CA University of Colorado, Program in Atmospheric and Oceanic Sciences & Laboratory for Atmospheric and Space Physics, Boulder, CO University of Colorado, Laboratory for Atmospheric and Space Physics, Boulder, CO
Virulence of infectious pancreatic necrosis virus (IPNV) isolates from Mexico

Infectious pancreatic necrosis virus (IPNV) causes economic losses in Mexican rainbow trout industry. In this study, virulence and genetic fingerprints of Mexican IPNV isolates was investigated for the first time. Two Mexican IPNV isolates were analyzed in rainbow trout fry and the Sp strain was included as high virulence. One of the Mexican IPNV isolate was obtained from diseased fish and the other from fish without clinical signs. The infection was performed using a standardized immersion. Clinical signs were observed at 4 days post infection in fry group infected with strain Sp, two days earlier than in trout infected with IPNV isolates Mexican. Severe lesions were found in 100% of the individuals of Sp group, but only in 25% of each isolated Mexican group. Results suggest that Mexican IPNV isolates are pathogenic, but less virulent than strain Sp. The amino acid motif residues of both Mexican isolates, corresponded to a subclinical disease. Nevertheless, the accumulated motility observed in the field, suggest that other factors play a role in the virulence of the disease.
Anomaly detection for machinery by using Big Data Real-Time processing and clustering technique

This paper aims to apply techniques of Big Data Analytics including K-Means Clustering to diagnose potential problems for offshore rotating machinery. The innovative methods are attempted in both Batch K-Means and Streaming K-Means. Their performances are compared with the conventional signal analysis method. Both K-Means models have a better performance on detecting significant mechanical faults as anomalies for offshore rotating machinery which can be considered as appropriate method for machine operational maintenance.
Iterative Decision-making for Evaluation of Adaptations (IDEA): A decision tree for balancing adaptation, fidelity, and intervention impact.

BACKGROUND Evidence-based practices (EBPs) are frequently adapted to maximize outcomes while maintaining fidelity to core EBP elements. Many step-by-step frameworks for adapting EBPs have been developed, but these models may not account for common complexities in the adaptation process. In this paper, we introduce the Iterative Decision-making for Evaluation of Adaptations (IDEA), a tool to guide adaptations that addresses these issues. FRAMEWORK DESIGN AND USE Adapting EBPs requires attending to key contingencies incorporated into the IDEA, including: the need for adaptations; fidelity to core EBP elements; the timeframe in which to make adaptations; the potential to collect pilot data; key clinical and implementation outcomes; and stakeholder viewpoints. We use two examples to illustrate application of the IDEA. CONCLUSIONS The IDEA is a practical tool to guide EBP adaptation that incorporates important decision points and the dynamism of ongoing adaptation. Its use may help implementation scientists, clinicians, and administrators maximize EBP impact.
Détection de communautés en ligne dans des graphes dynamiques

We introduce a novel algorithm of community detection that maintains dynamically a community structure of a large network that evolves with time. The algorithm maximizes the modularity index thanks to the construction of a randomized hierarchical clustering based on a Monte Carlo Markov Chain (MCMC) method. Interestingly, it could be seen as a dynamization of Louvain algorithm (see Blondel, Guillaume, Lambiotte et Lefebvre (2008)) where the aggregation step is replaced by the hierarchical instrumental probability.
P-selectin-deficient mice to study pathophysiology of sickle cell disease.

Sickle cell disease (SCD) is an autosomal-recessive genetic disorder that affects millions of people worldwide.1,2 Vaso-occlusion and hemolysis are the 2 predominant vascular events that contribute to the pathogenesis of SCD.3 Vaso-occlusion is believed to trigger acute systemic painful vaso-occlusive episode, which is the primary reason for emergency medical treatment of SCD patients.1,4 A role for P-selectin in promoting vaso-occlusion in the cremaster venules of SCD mice was first demonstrated by Kaul and Hebbel.5 Later, sickle erythrocytes were shown to adhere to P-selectin in vitro and undergo P-selectin–mediated rolling adhesion in postcapillary venules of mice in vivo, and P-selectin deletion or inhibition was shown to prevent adhesion of adoptively transferred sickle erythrocytes and vaso-occlusion in nonsickle mice in vivo.6-9 Also, platelet P-selectin–dependent neutrophil-platelet-erythrocyte heterocellular aggregates were shown to be significantly elevated in SCD patient blood.10 Epidemiological evidence suggests that a vaso-occlusive episode is often an antecedent to acute chest syndrome, a type of acute lung injury and one of the leading causes of mortality among SCD patients.1,11-13 Recently, we found that vaso-occlusive episode in transgenic humanized SCD mice triggered microembolism of precapillary pulmonary arterioles by platelet-neutrophil aggregates, which led to loss of blood flow in the lung microvasculature.13 Remarkably, platelet-neutrophil aggregates were attenuated, lung vaso-occlusion was prevented, and pulmonary blood flow was rescued in SCD mice following therapeutic blockade of P-selectin.13 A role for P-selectin in vaso-occlusion was further supported by a recent phase 2 study that reported a significant reduction in painful vaso-occlusive episodes among SCD patients receiving the P-selectin–blocking antibody crizanlizumab.14 Altogether, these findings suggest that SCD mice genetically deficient in P-selectin would be protected from vaso-occlusion. Such a mouse would also be useful in identifying the role of P-selectin in SCD-associated morbidities other than painful vaso-occlusive episode or acute chest syndrome.15 A role for P-selectin in systemic vaso-occlusion has been investigated using chimeric SCD mice lacking P-selectin only in the endothelium (intact in platelets),6,16 because SCD mice with global deletion of P-selectin did not exist. Here, we introduce the first SCD mice genetically lacking P-selectin in hematopoietic and nonhematopoietic compartments. Using our recently developed quantitative fluorescence intravital lung microscopy (qFILM)13,17 technique, we show that P-selectin deficiency protects SCD mice from lung vaso-occlusion.
Effect of alpha-lipoic acid on productive parameters and carcass quality in broiler chickens

Broilers production has been employed various additives, including antioxidants that have played an important role in it. Within these products, alpha lipoic acid (ALA) has distinguished; its addition in the diet provides different benefits to the animals. Therefore, the objective of this study was to evaluate the productive performance and meat quality of broilers with use of ALA in different doses (0, 40, 80, 160 and 320 ppm). The experiment was divided into two phases, the first productive performance was evaluated using 1,000 birds that were divided into five treatments with 200 animals each; the duration of this test was 49 d. In the second phase the sacrifice of animals was performed, 20 samples were obtained by treatment and testing the meat quality of them. The results of the production and quality meat variables were analyzed in a completely randomized design. No significant differences (P>0.05) were found by the addition of ALA on productive variables; however, chicks receiving 40 ppm of ALA lost less water by cooking.
School System and Educational Policy in a Highly Stratified Post-Soviet Society: The Importance of Social Context

This article presents the results of a study on Russian education policy. It explores how compulsory and secondary education meet contemporary social challenges, and how they should be adjusted to account for acute social inequality. The authors present evidence of the growing social polarization in post-Soviet Russia. This is discussed against the current situation in compulsory and secondary education, which is characterized by strong differentiation between schools in terms of their performance, enrollment, and availability of resources. They further discuss the possible impact of major turns in Russia’s education policy on the processes of social stratification, and whether it was effective enough to provide equal access to quality education for all social groups. The analysis concludes by making several suggestions about how education policy in Russia needs to be adjusted for it to become more targeted and relevant to the context in which its education institutions operate.
UvA-DARE ( Digital Academic Repository ) On the structure of the Medvedev lattice

We investigate the structure of the Medvedev lattice as a partial order. We prove that every interval in the lattice is either finite, in which case it is isomorphic to a finite Boolean algebra, or contains an antichain of size 2 א0 , the size of the lattice itself. We also prove that it is consistent with ZFC that the lattice has chains of size 2 א0 , and in fact that these big chains occur in every infinite interval. We also study embeddings of lattices and algebras. We show that large Boolean algebras can be embedded into the Medvedev lattice as upper semilattices, but that a Boolean algebra can be embedded as a lattice only if it is countable. Finally we discuss which of these results hold for the closely related Muchnik lattice. §
C1 neurons are part of the circuitry that recruits active expiration in response to the activation of peripheral chemoreceptors

Breathing results from the interaction of two distinct oscillators: the pre-Bötzinger Complex (preBötC), which drives inspiration; and the lateral parafacial region (pFRG), which drives active expiration. The pFRG is silent at rest and becomes rhythmically active during the stimulation of peripheral chemoreceptors, which also activates adrenergic C1 cells. We postulated that the C1 cells and the pFRG may constitute functionally distinct but interacting populations for controlling expiratory activity during hypoxia. We found in rats that: a) C1 neurons are activated by hypoxia and project to the pFRG region; b) active expiration elicited by hypoxia was blunted after blockade of ionotropic glutamatergic receptors at the level of the pFRG; and c) selective depletion of C1 neurons eliminated the active expiration elicited by hypoxia. These results suggest that C1 cells may regulate the respiratory cycle, including active expiration, under hypoxic conditions.
Late HIV diagnosis and missed opportunities for testing: piloting a standardised, multi-source review process

Late diagnosis of human immunodeficiency virus (HIV) (CD4 < 350) remains common in the UK and missed opportunities (MOs) for testing are often evident. National guidelines recommend HIV clinics conduct look-back reviews in all patients presenting late; however, a standardised methodology is not available and reviews are not routinely performed. This multi-centre audit reviewed all new, late HIV diagnoses across three centres in North East England. A standardised review process (incorporating a shared regional pathology system and summary care records) was used to identify MOs. Of 45 late diagnoses reviewed (median age 45 years, 76% male, median CD4 cell count 134), 28 (62%) had one or more MO, with a median of 18 months from MO to presentation. Sixty-two per cent of MOs occurred in primary care and most (82%) consisted of indicator conditions. At HIV presentation, 27 (60%) suffered moderate harm, 16 (36%) presented with acquired immune deficiency syndrome (AIDS) and 10 (22%) suffered severe harm, including 3 (7%) who died. Despite challenges in eliciting full medical records, the comprehensive review process described, which incorporates two regional electronic records, was more effective than previous methodologies and identified more MOs. Many people present with late HIV infection or AIDS and increased efforts are needed to improve testing.
Toxicity of Nanomaterials-Physicochemical Effects

Nanomaterials are the structures with at least one dimension of <100 nm. Recently, development in nanotechnology has led to use of nanomaterials in many different fields. On other hand, increasing in the use of nanomaterials has led to release of these materials to the environment. Therefore, before employing of these materials in biological and environmental and living systems, they should evaluate in terms of biocompatibility and distribution. Although the toxic effects of nanomaterials on living organisms, human health and the environment have been studied by some researchers, however, there are too much uncertainty about the effects and mechanisms of toxicity of nanomaterials. Therefore, understanding the toxicity effects of nanomaterials is highly desirable. Cellular uptake mechanisms and dispersion of nanomaterials in biological environments depend on their physicochemical properties. Therefore, knowledge the unique characteristics of nanomaterials and the interactions of nanomaterials with biological systems, are important criteria for the safe use of nanomaterials. Properties of nanomaterials such as size, shape, aspect ratio, density, and surface and structural defects and dissolving rate are the main cause of cytotoxicity and side effects of these materials in the body. Exposure to nanomaterials may be cause a range of acute and chronic effects, including inflammation, exacerbation of asthma, metal fume fever, fibrosis, chronic inflammatory diseases and cancer.
A new ground-based optical instrument to measure snowflakes

The properties of snowflakes such as their size distribution, fall velocity, axial ratio or their orientation when falling are important in modelling precipitation processes or in interpreting returned radar power, especially of polarized radar. The Institute of Atmospheric and Climate Science at the ETH has developed a ground-based optical spectrometer for the measurement of hydrometeors. The instrument works with two light beams which are vertically slightly offset. Thus, two images are recorded of each particle which can be used to calculate, in addition to the other properties, the exact fall velocity of the snowflakes. Hydrometeors can be recorded in the size range of 0.15 mm to 76 mm which includes also the very large snowflakes falling within or close to the melting layer without truncating their image.
Exploring Human Machine-Mediated Interaction for Applications in Social HRI

The objective of this study is to develop a robot behavioural model that includes non-verbal vocal information to produce behaviour that fits user expectation better. Our approach is to train the behavioural model using data representing humanhuman interaction during collaboration. The data, voice and user control inputs, are gathered during a game where players collaborate to navigate a character through a path. This paper presents the details of the approach undertaken to the data collection procedure as well as preliminary analysis of the data.
Significance of surface water in the terrestrial water budget: A case study in the Prairie Coteau using GRACE, GLDAS, Landsat, and groundwater well data

The terrestrial water budgets of the Prairie Coteau (PC; 38,000 km2) and Northern Glaciated Plains (NGP; 66,000 km2) regions of South Dakota, USA were characterized using a combination of in situ observations of groundwater and surface water, remote sensing estimates of terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE) and surface water changes from Landsat, and modeled changes in soil moisture, snow water equivalent, and total canopy water storage. In response to increased wetness in 2010 and 2011 over the region, prevalent surface water bodies accounted for a significant fraction of the terrestrial water budget of the PC, whereas the NGP, an area with sparse surface water, exhibited a greater increase in groundwater storage concomitant with enhanced seasonal variability. Over the study period from 2003 to 2011, GRACE‐based estimates of terrestrial water storage agreed well with combined groundwater, soil moisture, snow water equivalent, and total canopy water storage over the NGP, as surface water is not a significant component in this area. However, closure was improved over the PC if surface water changes were included in the water budget.
Opportunistic Beamforming in Wireless Network-on-Chip

Wireless Network-on-Chip (WNoC) has emerged as a promising alternative to conventional interconnect fabrics at the chip scale. Since WNoCs may imply the close integration of antennas, one of the salient challenges in this scenario is the management of coupling and interferences. This paper, instead of combating coupling, aims to take advantage of close integration to create arrays within a WNoC. The proposed solution is opportunistic as it attempts to exploit the existing infrastructure to build a simple reconfigurable beamforming scheme. Full-wave simulations show that, despite the effects of lossy silicon and nearby antennas, within-package arrays achieve moderate gains and beamwidths below 90°, a figure which is already relevant in the multiprocessor context.
Title A new transform-domain regularized recursive least M-estimatealgorithm for a robust linear estimation

This brief proposes a new transform-domain (TD) regularized M-estimation (TD-R-ME) algorithm for a robust linear estimation in an impulsive noise environment and develops an efficient QR-decomposition-based algorithm for recursive implementation. By formulating the robust regularized linear estimation in transformed regression coefficients, the proposed TD-R-ME algorithm was found to offer better estimation accuracy than direct application of regularization techniques to estimate system coefficients when they are correlated. Furthermore, a QR-based algorithm and an effective adaptive method for selecting regularization parameters are developed for recursive implementation of the TD-R-ME algorithm. Simulation results show that the proposed TD regularized QR recursive least M-estimate (TD-R-QRRLM) algorithm offers improved performance over its least squares counterpart in an impulsive noise environment. Moreover, a TD smoothly clipped absolute deviation R-QRRLM was found to give a better steady-state excess mean square error than other QRRLM-related methods when regression coefficients are correlated.