Miracle-dz/UniFAR-FTUs huggingface dataset:
Consumption of Antimicrobials in Pigs, Veal Calves, and Broilers in The Netherlands: Quantitative Results of Nationwide Collection of Data in 2011

In 2011, Dutch animal production sectors started recording veterinary antimicrobial consumption. These data are used by the Netherlands Veterinary Medicines Authority to create transparency in and define benchmark indicators for veterinary consumption of antimicrobials. This paper presents the results of sector wide consumption of antimicrobials, in the form of prescriptions or deliveries, for all pig, veal calf, and broiler farms. Data were used to calculate animal defined daily dosages per year (ADDD/Y) per pig or veal calf farm. For broiler farms, number of animal treatment days per year was calculated. Furthermore, data were used to calculate the consumption of specific antimicrobial classes per administration route per pig or veal calf farm. The distribution of antimicrobial consumption per farm varied greatly within and between farm categories. All categories, except for rosé starter farms, showed a highly right skewed distribution with a long tail. Median ADDD/Y values varied from 1.2 ADDD/Y for rosé finisher farms to 83.2 ADDD/Y for rosé starter farms, with 28.6 ADDD/Y for white veal calf farms. Median consumption in pig farms was 9.3 ADDD/Y for production pig farms and 3.0 ADDD/Y for slaughter pig farms. Median consumption in broiler farms was 20.9 ATD/Y. Regarding specific antimicrobial classes, fluoroquinolones were mainly used on veal calf farms, but in low quantities: P75 range was 0 – 0.99 ADDD/Y, and 0 – 0.04 ADDD/Y in pig farms. The P75 range for 3rd/4th-generation cephalosporins was 0 – 0.07 ADDD/Y for veal calf farms, and 0 – 0.1 ADDD/Y for pig farms. The insights obtained from these results, and the full transparency obtained by monitoring antimicrobial consumption per farm, will help reduce antimicrobial consumption and endorse antimicrobial stewardship. The wide and skewed distribution in consumption has important practical and methodological implications for benchmarking, surveillance and future analysis of trends.
On two probabilistic decoding algorithms for binary linear codes

A generalization of the Sullivan inequality (1967) on the ratio of the probability of a linear code to that of any of its cosets is proved. Starting from this inequality, a sufficient condition for successful decoding of linear codes by a probabilistic method is derived. A probabilistic decoding algorithm for low-density parity-check codes is also analyzed. This method of analysis enables one to estimate experimentally the probability of successful decoding for any given linear code and for any chosen family of parity-check sets. Using the example of a linear (512,100) code, the author illustrates the dependence of the successful probability on the channel noise level. >
Detecting coevolving positions in a molecule: why and how to account for phylogeny

Positions in a molecule that share a common constraint do not evolve independently, and therefore leave a signature in the patterns of homologous sequences. Exhibiting such positions with a coevolution pattern from a sequence alignment has great potential for predicting functional and structural properties of molecules through comparative analysis. This task is complicated by the existence of additional correlation sources, leading to false predictions. The nature of the data is a major source of noise correlation: sequences are taken from individuals with different degrees of relatedness, and who therefore are intrinsically correlated. This has led to several method developments in different fields that are potentially confusing for non-expert users interested in these methodologies. It also explains why coevolution detection methods are largely unemployed despite the importance of the biological questions they address. In this article, I focus on the role of shared ancestry for understanding molecular coevolution patterns. I review and classify existing coevolution detection methods according to their ability to handle shared ancestry. Using a ribosomal RNA benchmark data set, for which detailed knowledge of the structure and coevolution patterns is available, I demonstrate and explain why taking the underlying evolutionary history of sequences into account is the only way to extract the full coevolution signal in the data. I also evaluate, using rigorous statistical procedures, the best approaches to do so, and discuss several important biological aspects to consider when performing coevolution analyses.
Household Air Pollution Intervention Implications: Findings from Qualitative Studies and a Field Trial of Clean Cookstoves in Two Rural Villages in India

Exposure to household air pollution is estimated to be the 3rd largest contributor to the global burden of disease and the largest contributor in South Asia. Unacceptability of improved cook stoves by the intended user has been identified as a crucial factor hindering uptake and sustained use. We conducted a qualitative study to understand the socio-cultural factors that influence acceptance of improved cookstoves and conducted a systematic field trial in two rural villages in Maharashtra, India. The qualitative study used semi-structured in-depth interviews and focus group discussions. We included women primarily responsible for household cooking, their husbands, senior women in their households, and community health workers. We also conducted kitchen observations. The results indicated low awareness and knowledge of the health risks associated with traditional cookstove use although high prevalence of household air pollution (HAP) exposure symptoms among all groups. Women were resigned to using traditional cookstoves although they did not like them. The field trial findings were dominated by responses concerned with convenience and health advantages. We identify important issues to be considered when introducing an improved cookstove programme that will increase acceptability and potentially sustained used of improved cookstoves.
Data Mining Technologies for Blood Glucose and Diabetes Management

Data mining is the process of selecting, exploring, and modeling large amounts of data to discover unknown patterns or relationships useful to the data analyst. This article describes applications of data mining for the analysis of blood glucose and diabetes mellitus data. The diabetes management context is particularly well suited to a data mining approach. The availability of electronic health records and monitoring facilities, including telemedicine programs, is leading to accumulating huge data sets that are accessible to physicians, practitioners, and health care decision makers. Moreover, because diabetes is a lifelong disease, even data available for an individual patient may be massive and difficult to interpret. Finally, the capability of interpreting blood glucose readings is important not only in diabetes monitoring but also when monitoring patients in intensive care units. This article describes and illustrates work that has been carried out in our institutions in two areas in which data mining has a significant potential utility to researchers and clinical practitioners: analysis of (i) blood glucose home monitoring data of diabetes mellitus patients and (ii) blood glucose monitoring data from hospitalized intensive care unit patients.
Automotive Ethernet in On-Board Diagnosis (Over IP) & in-vehicle networking

This paper demonstrates the architecture of an Ethernet prototype platform for On-Board Diagnostic System (OBD) and a camera based application using an ARM centred system. Driver is also provided with a user interface through which user can read any of the sensor values by selecting on the list. Diagnosis of faults in parameters, notification of sudden changes to the driver, and indication regarding the reason for the fault are included in the system setup. The driver can find out the faults in car on the spot and this does not require an OBD scan tool for it. If in case the vehicle got struck in remote areas, the proposed OBD system inside the vehicle can be connected to the vehicle service centre by providing internet facility. This paper focuses on a migration concept for replacing todays employed CAN-buses by Ethernet/IP-based networks.
Cell-Based Screen Identifies Human Interferon-Stimulated Regulators of Listeria monocytogenes Infection

The type I interferon (IFN) activated transcriptional response is a critical antiviral defense mechanism, yet its role in bacterial pathogenesis remains less well characterized. Using an intracellular pathogen Listeria monocytogenes (Lm) as a model bacterial pathogen, we sought to identify the roles of individual interferon-stimulated genes (ISGs) in context of bacterial infection. Previously, IFN has been implicated in both restricting and promoting Lm growth and immune stimulatory functions in vivo. Here we adapted a gain-of-function flow cytometry based approach to screen a library of more than 350 human ISGs for inhibitors and enhancers of Lm infection. We identify 6 genes, including UNC93B1, MYD88, AQP9, and TRIM14 that potently inhibit Lm infection. These inhibitors act through both transcription-mediated (MYD88) and non-transcriptional mechanisms (TRIM14). Further, we identify and characterize the human high affinity immunoglobulin receptor FcγRIa as an enhancer of Lm internalization. Our results reveal that FcγRIa promotes Lm uptake in the absence of known host Lm internalization receptors (E-cadherin and c-Met) as well as bacterial surface internalins (InlA and InlB). Additionally, FcγRIa-mediated uptake occurs independently of Lm opsonization or canonical FcγRIa signaling. Finally, we established the contribution of FcγRIa to Lm infection in phagocytic cells, thus potentially linking the IFN response to a novel bacterial uptake pathway. Together, these studies provide an experimental and conceptual basis for deciphering the role of IFN in bacterial defense and virulence at single-gene resolution.
A functional model of silicon carbide JFET and its use in the analysis of switching-transient and impact of gate resistor, miller effect and parasitic inductance

A functional model of silicon carbide (SiC) JFET was developed to study its performance. Based on this model, the gate resistor in the gate drive circuit of SiC JFET is optimised with comprehensive consideration of gate current impact, miller effect, switching speed and voltage spikes. The switch on oscillation caused by parasitic inductance is analysed and methods are proposed to mitigate the oscillation. Experiments on a 300 V prototype validated the proposed model.
A stochastic framework for optimal key frame extraction from MPEG video databases

A framework for video content representation is proposed in this paper for extracting limited, but meaningful, information of video data directly from MPEG compressed domain. First, the traditional frame-based representation is transformed to a feature-based one. Then, all features are gathered together using a fuzzy formulation and extraction of several key frames is performed for each shot in a content-based rate sampling framework. In particular, our approach is based on minimization of a cross-correlation criterion among video frames of a given shot so as to be located a set of minimally correlated feature vectors. Experimental results indicating the good performance of the proposed scheme are also presented.
UvA-DARE ( Digital Academic Repository ) Clinical aspects of uterine artery embolization

Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva. nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.
UvA-DARE ( Digital Academic Repository ) Using Informative Behavior to Increase Engagement While Learning from Human Reward

In this work, we address a relatively unexplored aspect of designing agents that learn fromhuman reward.We investigate howan agent’s non-task behavior can affect a human trainer’s training and agent learning. We use the TAMER framework, which facilitates the training of agents by human-generated reward signals, i.e., judgements of the quality of the agent’s actions, as the foundation for our investigation. Then, starting from the premise that the interaction between the agent and the trainer should be bi-directional, we propose two new training interfaces to increase a human trainer’s active involvement in the training process and thereby improve the agent’s task performance. One provides information on the agent’s uncertainty which is a metric calculated as data coverage, the other on its performance. Our results from a 51-subject user study show that these interfaces can induce the trainers to train longer and give more feedback. The agent’s performance, however, increases only in response to the addition of performance-oriented information, not by sharing uncertainty levels. These results suggest that the organizational maxim about human behavior, “you get what you measure”—i.e., sharing metrics with people causes them to focus on optimizing those metrics while de-emphasizing other objectives—also applies to the training of agents. Using principle component analysis, we show how trainers in the two conditions train agents differently. In addition, by simulating the influence of the agent’s uncertainty–informative B Guangliang Li g.li@uva.nl Shimon Whiteson shimon.whiteson@cs.ox. ac.uk W. Bradley Knox bradknox@mit.edu Hayley Hung h.hung@tudelft.nl 1 University of Amsterdam, Amsterdam, The Netherlands 2 University of Oxford, Oxford, UK 3 Massachusetts Institute of Technology, Cambridge, USA 4 Technical University of Delft, Delft, The Netherlands
Chronic imaging of cortical sensory map dynamics using a genetically encoded calcium indicator

Non‐technical summary Optical imaging is widely used to map functional areas of the cerebral cortex. We present a method for fast fluorescence imaging of map‐level cortical activity using a calcium indicator protein. Sensory‐evoked neuronal activity can be imaged repeatedly in the same mouse over weeks, enabling new opportunities for the longitudinal study of cortical function and dysfunction. We hope this method will be flexibly applied across different cortical areas and to a variety of newly developed genetically encoded calcium and voltage sensors.
Fault identification in networks by passive testing

We employ the finite state machine (FSM) model for networks to investigate fault identification using passive testing. First we introduce the concept of passive testing. Then, we introduce the FSM model with necessary assumptions and justification. We introduce the fault model and the fault detection algorithm using passive testing. Extending this result, we develop the theorems and algorithms for fault identification. An example is given illustrating our approach. Then, extensions to our approach are introduced to achieve better fault identification. We then illustrate our technique through a simulation of a practical X.25 example. Finally future extensions and potential trends are discussed.
Case–control study of anaemia among middle-aged and elderly women in three rural areas of China

Objectives To propose a feasible suggestion to reduce the high prevalence of anaemia in middle-aged and elderly women by investigating risk factors, particularly nutritional factors, and analysing the effect on anaemia in three different rural areas of China. Design A case–control study. Setting Three counties of China. Participants Women aged 50–75 years in the three counties. Main outcome measures Adjusted OR (95% CI) of anaemia associated with diet, lifestyle and blood biochemical indices. Results Compared with controls, women with anaemia had lower body mass index (22.1 (3.2) kg/m2 vs 23.2 (3.5) kg/m2; p<0.001), a higher experience of shortage of food (45.0% vs 36.5%; p<0.001), less soy food intake (0.5 (0.3, 26.7) g/day vs 5.6 (0.4, 27.8) g/day; p<0.048), lower serum iron (13.4 (5.4) μmol/L vs 16.4 (5.7) μmol/L; p<0.001), lower ferritin (109.6 (85.6) ng/mL vs 131.0 (92.0) ng/mL; p<0.001), lower transferrin saturation levels (22.5 (9.5)% vs 26.8 (9.6)%; p<0.001) and higher levels of free erythrocyte protoporphyrin (42.4 (21.2) μg/dL vs 39.6 (17.8) μg/dL; p<0.001). Anaemia was significantly associated with BMI(OR=0.90, 95% CI (0.87 to 0.92)), food shortage experience (OR=1.39, 95% CI (1.15 to 1.69)), total protein (OR=0.66, 95%CI (0.54 to 0.80)), Albumin (OR=0.72, 95%CI (0.59 to 0.87)) in univariate analysis. Multivariate analysis showed that body mass index, experience of food shortage, total protein and albumin were independently related to anaemia. Conclusions Among middle-aged and elderly women in rural China, the nutrition status of anaemic cases is far below that of controls. Lower body mass index and a greater experience of food shortage are closely related to anaemia. Improving the blood protein status by consuming protein-sufficient foods such as soy food is a feasible approach for elderly anaemic women. Further research is needed on the effect of chronic inflammation and infectious disease on anaemia in elderly women in rural China.
Timing-test scheduling for constraint-graph based post-silicon skew tuning

Post-Silicon Tuning is an emerging technology for improving performance-yield of VLSIs under process variations. This paper focuses especially on the post-silicon timing-skew tuning (PSST) via programmable delay elements (PDEs), and proposes a novel tuning algorithm which utilizes only the result of setup and hold timing tests, not the result of costly delay-time measurements. The basic framework of our PSST consists of the construction of Control-value Constraint Graph from the results of timing-tests, and the computation of longest path lengths on this graph for finding safe PDE setting. Even though the cost for timing test is smaller than a delay-time measurement, the cost of timing-tests is still a dominant part of the PSST cost, and its reduction is a crucial problem. Longest path lengths which we need to compute depends directly on edge weights in the “longest-paths tree”, but for co-tree edges, their exact edge weights are not always necessary. Based on this observation, we propose timing-test scheduling for reducing the timing-test cost for PDE tuning. The experimental simulation results show that our approach reduces the test cost by almost half or more.
Analysis of Subthreshold Leakage Current using Stack and VTCMOS Techniques for Ultra Low Power Cell Design

To meet the ever-increasing demand of high performance systems, more and more functions are integrated into single chip by scaling down the size of device. As a result of high density circuits chip, the growing magnitude of power consumption per unit area and thus the heat removal and cooling are becoming limiting factors for further scaling and performance improvement of the systems. The power dissipation due to subthreshold leakage current becomes comparable to switching or dynamic power component and is a serious concern for circuit designing in deep submicron region. Many techniques are used to reduce the leakage current and to minimize the power consumption in standby mode. This paper shows a comparative analysis of two techniques namely stacked transistor and VTCMOS (Variable Threshold CMOS) method used to reduce the subthreshold leakage current. The different combinational cells were implemented using IBM 90 nanometer technology. The 1.32V supply voltage was applied and layouts of the cells were simulated using Cadence Design systems SPECTRE simulator. The results show that cells designed using VTCMOS technique has less leakage current than stacked transistor and conventional methods.
A Novel Method for Background Suppression in Millimeter-Wave Traffic Radar Sensor

The millimeter-wave traffic flow detection radars have been widely used in traffic information collection systems during these years in China. To improve the detection accuracy of the traffic radar sensor, background suppression is of great necessity and importance. In this paper, after analyzing the principles of the millimeter-wave traffic radar sensor and the properties of the echo power, we propose a novel method for background suppression. The proposed algorithm is on the basis of order statistics and coherent averaging. Moreover, we present the field test results in different road conditions, and additionally compare the algorithm with previous approaches. Consistency of the test results with the theory proves the feasibility of the proposed algorithm. And the capacity for background suppression of the traffic radar sensor has been noticeably improved.
Unequal Power Allocation of Image Transmission in OFDM Systems

The OFDM technique with cyclic time guard, which has been proposed for broadband communications, is an increasing approach to combat the frequency selectivity of the channel. In this paper, a modified OFDM scheme for image transmission is proposed. The new proposal is based on modification of the OFDM structure through using unequal power allocation for the successive OFDM symbols. Unequal cyclic time guard is also applied with unequal power allocation. The proposed method is compared with the conventional OFDM. Results show that the performance is improved at lower average cyclic extension periods and a lower average power when using the proposed method. The performance study of OFDM scheme is examined with and without forward error correction (FEC).
Human Perception of Haptic Force Direction

In this paper we investigate the accuracy of human perception of haptic force direction applied to the hand. Haptic interfaces are commonly used in many applications and understanding the limitations of human perception would facilitate the design of these interfaces and the associated applications. The literature contains work related to force perception; however, none of which address the issue of the accuracy of haptic force direction perception. We discuss the design and implementation of the experiment used to evaluate the accuracy. Also presented are results related to training effects, fatigue and accuracy across angular regions
Challenges for Professional Development of Mother Teacher Educators in Information Communication Technologies

Information and Communication Technologies (ICT) have brought new possibilities to the education sector, but at the same time, they have placed more demands on teachers. They now have to learn how to cope with computers in their classrooms, how to compete with students in accessing the vast body of information chiefly via internet and how to use the hardware and software to enhance the teaching/learning process. Therefore the teachers have to spend more time for their Professional Development in order to reach the benefits of ICT to the learners. Ability of teachers in the uses of ICT for education entails sharing of knowledge among teacher educators, intra and Inter-institutional collaboration, and support from principals and administrators. These factors must be in place for the mother teacher educators, accepting their problems and stress they face in order to bring change in the classroom they handle through ICT. Mother teacher educators require ongoing support and opportunities to experiment with new skills and strategies over time. A professional development programme should therefore include more time and special provisions for developing leadership skills, such as decision-making, team building, communicating, and problem solving for mother teachers considering stress factors. Mothers Teachers Professional Development in ICT therefore face number of challenges. This paper discusses various critical components and challenges for professional development of mother teacher educators in ICT.