Miracle-dz/UniFAR-FTUs huggingface dataset:
A frequency-selective nested dual-loop broadband low-noise amplifier in 90 nm CMOS

A broadband, frequency-selective low-noise amplifier (LNA) with at least 25 dB of rejection at frequencies below the L-band (includes GPS and GSM carriers) is fabricated in a 90 nm standard CMOS process. The proposed LNA can be used for broadband impulse-radio ultra-wideband (IR-UWB) and frequency modulated FM-UWB. The frequency-selective (3.5-10.5 GHz) LNA is power-to-current (P-I) configured and comprises nested reactive feedback loops: a positive current-to-current (I-I) feedback loop to boost the power gain and a negative I-I feedback loop for impedance and noise matching. The measured gain of the P-I LNA is 15±3 dB. It has a noise figure (NF) of 2.4±0.8 dB and a 1-dB gain compression point (P-½dB) of -17.5±2.5 dBm. The die area of the LNA is 0.7×0.8 mm2 and it consumes 9.6 mW from a 0.8 V power supply. The proposed P-I LNA is most suitable for a sub-1 V single-cell radios.
Keep it simple: Is deep learning good for linguistic smell detection?

Deep neural networks is a popular technique that has been applied successfully to domains such as image processing, sentiment analysis, speech recognition, and computational linguistic. Deep neural networks are machine learning algorithms that, in general, require a labeled set of positive and negative examples that are used to tune hyper-parameters and adjust model coefficients to learn a prediction function. Recently, deep neural networks have also been successfully applied to certain software engineering problem domains (e.g., bug prediction), however, results are shown to be outperformed by traditional machine learning approaches in other domains (e.g., recovering links between entries in a discussion forum). In this paper, we report our experience in building an automatic Linguistic Antipattern Detector (LAPD) using deep neural networks. We manually build and validate an oracle of around 1,700 instances and create binary classification models using traditional machine learning approaches and Convolutional Neural Networks. Our experience is that, considering the size of the oracle, the available hardware and software, as well as the theory to interpret results, deep neural networks are outperformed by traditional machine learning algorithms in terms of all evaluation metrics we used and resources (time and memory). Therefore, although deep learning is reported to produce results comparable and even superior to human experts for certain complex tasks, it does not seem to be a good fit for simple classification tasks like smell detection. Researchers and practitioners should be careful when selecting machine learning models for the problem at hand.
A Student’s t Mixture Probability Hypothesis Density Filter for Multi-Target Tracking with Outliers

In multi-target tracking, the outliers-corrupted process and measurement noises can reduce the performance of the probability hypothesis density (PHD) filter severely. To solve the problem, this paper proposed a novel PHD filter, called Student’s t mixture PHD (STM-PHD) filter. The proposed filter models the heavy-tailed process noise and measurement noise as a Student’s t distribution as well as approximates the multi-target intensity as a mixture of Student’s t components to be propagated in time. Then, a closed PHD recursion is obtained based on Student’s t approximation. Our approach can make full use of the heavy-tailed characteristic of a Student’s t distribution to handle the situations with heavy-tailed process and the measurement noises. The simulation results verify that the proposed filter can overcome the negative effect generated by outliers and maintain a good tracking accuracy in the simultaneous presence of process and measurement outliers.
Searching for the Definition of Macrosomia through an Outcome-Based Approach

Background Macrosomia has been defined in various ways by obstetricians and researchers. The purpose of the present study was to search for a definition of macrosomia through an outcome-based approach. Methods In a study of 30,831,694 singleton term live births and 38,053 stillbirths in the U.S. Linked Birth-Infant Death Cohort datasets (1995–2004), we compared the occurrence of stillbirth, neonatal death, and 5-min Apgar score less than four in subgroups of birthweight (4000–4099 g, 4100–4199 g, 4200–4299 g, 4300–4399 g, 4400–4499 g, 4500–4999 g vs. reference group 3500–4000 g) and birthweight percentile for gestational age (90th–94th percentile, 95th-96th, and ≥97th percentile, vs. reference group 75th–90th percentile). Results There was no significant increase in adverse perinatal outcomes until birthweight exceeded the 97th percentile. Weight-specific odds ratios (ORs) elevated substantially to 2 when birthweight exceeded 4500 g in Whites. In Blacks and Hispanics, the aORs exceeded 2 for 5-min Apgar less than four when birthweight exceeded 4300 g. For vaginal deliveries, the aORs of perinatal morbidity and mortality were larger for most of the subgroups, but the patterns remained the same. Conclusions A birthweight greater than 4500 g in Whites, or 4300 g in Blacks and Hispanics regardless of gestational age is the optimal threshold to define macrosomia. A birthweight greater than the 97th percentile for a given gestational age, irrespective of race is also reasonable to define macrosomia. The former may be more clinically useful and simpler to apply.
Applied co-simulation of intelligent power systems : implementation , usage , examples

Smart Grids link various types of energy technologies such as power electronics, machines, grids, and markets via communication technology, which leads to trans-disciplinary, multi-domain system. Simulation packages for assessing system integration of components typically cover only one sub-domain, while terribly simplifying the others. Co-simulation overcomes this by coupling sub-domain models that are described and solved within their native environments, using specialized solvers and validated libraries. This article discusses the state of the art and conceptually describes the main challenges for simulating intelligent power systems. Part 1 covers fundamental concepts, part 2 applications.
Skills education on knowledge of obstetric danger signs , birth preparedness , utilization of skilled care and male involvement A Community-based intervention study in rural

August, F. 2016. Effect of Home Based Life Saving Skills education on knowledge of obstetric danger signs, birth preparedness, utilization of skilled care and male involvement. A Community-based intervention study in rural Tanzania. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1174. 76 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9457-5. Use of skilled care during antenatal visits and delivery is recommended to address the burden of maternal mortality. However there are few facility deliveries and insufficient knowledge of danger signs, especially in rural Tanzania. The aim of this thesis was to explore the perceptions and challenges that the community faces while preparing for childbirth and to evaluate an intervention of the Home Based Life Saving Skills education programme on knowledge of danger signs, facility delivery and male involvement when delivered by rural community health workers in Tanzania. In Paper I, Focus Group Discussions explored the perceptions and challenges that the community encounters while preparing for childbirth. Structured questionnaires assessed men’s knowledge of danger signs and birth preparedness and complication readiness in Paper II. The effect of the Home Based Life Saving Skills education programme in the community was assessed with a before-and-after evaluation in two districts; one intervention and one comparison. Paper III assessed the effect of the programme on knowledge of danger signs and birth preparedness and facility delivery among women, while Paper IV evaluated its effect on male involvement. The community perceived that all births must be prepared for and that obstetric complication demands hospital care; hence skilled care was favoured. Men’s knowledge of danger signs was limited; only 12% were prepared for childbirth and complications. Preparedness was associated with knowledge of obstetric complications (AOR=1.4 95% CI 1.8 – 2.6). The intervention showed women utilizing antenatal care (four visits) significantly more (43.4 vs 67.8%) with a net effect of 25.3% (95% CI: 16.9 – 33.2; p < .0001). The use of facility delivery improved in the intervention area (75.6 vs 90.2%; p = 0.0002), but with no significant net effect 11.5% (95% CI: -5.1 – 39.6; p = 0.123) when comparing the two districts. Male involvement improved (39.2% vs 80.9%) with a net intervention effect of 41.1% (CI: 28.5 – 53.8; p < .0001). Improvements were demonstrated in men’s knowledge level, in escorting partners for antenatal care and delivery, making birth preparations, and shared decision-making. The intervention, in educating this rural community, is effective in improving knowledge, birth preparedness, male involvement and use of skilled care.
Digital Adaptive Calibration of Multi-Step Analog to Digital Converters

Digital Adaptive Calibration of Multi-Step Analog to Digital Converters Amir Zjajo1 ∗, Manuel J. Barragan2, and Jose Pineda de Gyvez3 4 1Circuits and Systems Group, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands 2Institute of Microelectronics, University of Sevilla, Av. Americo Vespucio s/n, 41092, Sevilla, Spain 3NXP Semiconductors, High Tech Campus 32, 5656 AE, Eindhoven, The Netherlands 4Electronic Systems Group, Eindhoven University of Technology, Den Dolech 2, 5600 MB, Eindhoven, The Netherlands
The laboratory diagnosis of Strongyloides stercoralis

Matthew R Watts, Gemma Robertson and Richard S Bradbury Centre for Infectious Diseases and Microbiology, Pathology West – ICMPR, and Marie Bashir Institute, University of Sydney, Westmead Hospital, Westmead, Sydney, NSW, Australia, Tel: +61 2 9845 6255, Email: matthew.watts@health.nsw. gov.au Melbourne Pathology, Collingwood and James Cook University, Tel: +61 3 9287 7700, Email: gemmajrobertson@gmail.com School of Medical and Applied Sciences, Central Queensland University, Rockhampton, Qld, Australia Corresponding author. Email: r.bradbury@cqu.edu. au
Windows to the Brain

Cover. Images show serotonin receptor binding overlaid on a magnetic resonance image in a control subject (left) and apparent diffusion coefficient changes in an abstinent ecstasy user (right). The approximate location of the axial sections is marked on the sagittal magnetic resonance image. Figure 1. Diffusion-weighted imaging. In a recent study the apparent diffusion coefficient (ADC) was significantly higher in 8 ecstasy users (abstinent for at least 3 weeks), as compared with control subjects, in many regions (green), including the globus pallidus and cingulate cortex. (Reprinted, with permission, from Reneman et al.)
A Temperature-Hardened Sensor Interface with a 12-Bit Digital Output Using a Novel Pulse Width Modulation Technique

A fully integrated sensor interface for a wide operational temperature range is presented. It translates the sensor signal into a pulse width modulated (PWM) signal that is then converted into a 12-bit digital output. The sensor interface is based on a pair of injection locked oscillators used to implement a differential time-domain architecture with low sensitivity to temperature variations. A prototype has been fabricated using a 180 nm partially depleted silicon-on-insulator (SOI) technology. Experimental results demonstrate a thermal stability as low as 65 ppm/°C over a large temperature range from −20 °C up to 220 °C.
Microstructural brain abnormalities, affective temperaments, and suicidal behavior in patients with major depression

According to magnetic resonance imaging (MRI) studies, brain white matter (WM) abnormalities have been suggested to play a critical role in the pathogenesis of major depressive disorder (MDD) and related suicidal behavior. However, MRI findings may be limited by low spatial resolution; therefore, an important contribution to the understanding of the role and significance of WM alterations derived by the development of the most recent magnetic resonance techniques, such as diffusion tensor imaging (DTI). Several DTI studies reported an association between altered WM integrity and MDD/suicidal behavior. Microstructural WM abnormalities may be located in neural circuits critically implicated in emotional processes and mood regulation resulting in enhanced vulnerability to psychiatric morbidity. WM abnormalities detected using DTI may contribute to functional deficits and help to clarify the pathophysiological mechanisms underlying MDD as well as suicidal behavior. By a clinical point of view, research also suggested that affective temperaments may play a relevant role in the psychopathological characteristics of mood disorders, clinical trajectory of episodes and polarity, long-term outcome and suicidality. Unfortunately, only few studies investigated the association between affective temperaments and WM abnormalities and discussed their possible implications in patients with MDD and suicidal behavior. Using a comprehensive search of Medline database, the aim of the present study was to critically review the current literature on the association between WM alterations as assessed by MRI and DTI techniques, affective temperaments, MDD and suicidal behavior.
Assembly Rules for Generalized Lotka-Volterra Equations

In food webs, many interacting species coexist despite the restrictions imposed by the competitive exclusion principle and apparent competition. For the generalized Lotka-Volterra equations, sustainable coexistence necessitates nonzero determinant of the interaction matrix. Here we show that this requirement is equivalent to demanding that each species be part of a non-overlapping pairing, which substantially constrains the food web structure. We demonstrate that a stable food web can always be obtained if a non-overlapping pairing exists. If it does not, the matrix rank can be used to quantify the lack of niches, corresponding to unpaired species. For the species richness at each trophic level, we derive the food web assembly rules, which specify sustainable combinations. In neighboring levels, these rules allow the higher level to avert competitive exclusion at the lower, thereby incorporating apparent competition. In agreement with data, the assembly rules predict high species numbers at intermediate levels and thinning at the top and bottom. Using comprehensive food web data, we demonstrate how omnivores or parasites with hosts at multiple trophic levels can loosen the constraints and help obtain coexistence in food webs. Hence, omnivory may be the glue that keeps communities intact even under extinction or ecological release of species.
Characterization of milk composition and somatic cell count estimates from automatic milking systems sensors

Adoption of automatic milking systems (AMS) is increasing rapidly in Canada. Some AMS are equipped with sensors to estimate milk components (i.e., fat, protein and lactose) and somatic cell count (SCC). However, the accuracy of the estimates produced by these sensors is unknown. For these data to be used for herd management, benchmarking and genetic evaluations, it is important to get a better understanding of how this data compares with traditional milk recording laboratory analyses.
Sensitivity to Serial Dependency of Input Processes: A Robust Approach

Procedures in assessing the impact of serial dependency on performance analysis are usually built on parametrically specified models. In this paper, we propose a robust, nonparametric approach to carry out this assessment, by computing the worst-case deviation of the performance measure due to arbitrary dependence. The approach is based on optimizations, posited on the model space, that have constraints specifying the level of dependency measured by a nonparametric distance to some nominal i.i. d. input model. We study approximation methods for these optimizations via simulation and analysis-of-variance (ANOVA). Numerical experiments demonstrate how the proposed approach can discover the hidden impacts of dependency beyond those revealed by conventional parametric modeling and correlation studies.
Application of Bacteriophage in Biocontrol of Major Foodborne Bacterial Pathogens

Bacteriophages are viruses of bacteria that can be applied as pre-harvest and post-harvest interventions in food to reduce the foodborne pathogens. The increasing incidence of foodborne illnesses and prevalence of antibioticresistant bacteria have led to the use of phage as an alternative biocontrol agent in food industry to assure the safety of the food products. A number of studies have shown the potential of bacteriophages in controlling various foodborne pathogens within food animals and also the raw and processed foods. This paper reviews the potential use of bacteriophages in biocontrol of the major foodborne bacterial pathogens (Salmonella, Campylobacter, E. coli O157: H7 and Listeria monocytogenes) in food animals and food processing. Furthermore, the advantages and limitations of bacteriophages as biocontrol agent in foods were described in this paper as well.
A Cross-Language Study of Decontextualized Vocabulary Comprehension in Toddlerhood and Kindergarten Readiness

Recent studies demonstrate that emerging literacy depends on earlier language achievement. Importantly, most extant work focuses on parent-reported production prior to 30 months of age. Of interest is whether and how directly assessed vocabulary comprehension in the 2nd year of life supports vocabulary and kindergarten readiness in the 4th year. We first contrasted orthogonal indices of parent-reported production and directly assessed vocabulary comprehension and found that comprehension was a stronger predictor of child outcomes. We then assessed prediction from vocabulary comprehension controlling for maternal education, preschool attendance, and child sex. In 3 studies early, decontextualized vocabulary comprehension emerged as a significant predictor of 4th year language and kindergarten readiness accounting for unique variance above demographic control variables. Further we found that the effect of early vocabulary on 4th year kindergarten readiness was not mediated by 4th year vocabulary. This pattern of results emerged in English monolingual children (N = 48) and replicated in French monolingual (N = 58) and French–English bilingual children (N = 34). Our findings suggest that early, decontextualized vocabulary may provide a platform for the establishment of a conceptual system that supports both later vocabulary and kindergarten readiness, including the acquisition of a wide range of concepts including print and number. Differences between parent-reported and directly assessed vocabulary and the mechanisms by which decontextualized vocabulary may contribute to conceptual development are discussed.
A Scoring System to Predict Unplanned Intubation in Patients Having Undergone Major Surgical Procedures

BACKGROUND: Unplanned tracheal intubation after surgery has been associated with high mortality. Few studies have examined the risk factors for this complication. METHODS: The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) is a multicenter, prospective, outcome-oriented database for patients having undergone major surgical procedures. Using the NSQIP data for the years 2005 to 2007 (n = 231,548) and Cox proportional hazards modeling, we identified risk factors and used them to derive a scoring system to stratify patients' risk of having an unplanned intubation outcome. NSQIP data for the year 2008 (n = 176,031) were then used to validate the scoring system. RESULTS: The variables most predictive of unplanned intubation were patient age (0–4 points), ASA physical status (0–7 points), the presence of preoperative sepsis (3 points), and total operative time (0–4 points). The Unplanned Intubation Risk Index based on the adjusted hazard ratios for these variables, ranging from 0 (lowest risk) to 18 (highest risk), had a 79% accuracy in distinguishing patients requiring unplanned intubation from those not requiring it (area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.79–0.80). When the scoring system was applied to the validation cohort data, its discriminative performance remained virtually unchanged (area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.79–0.80). CONCLUSIONS: A scoring system based on clinical risk factors was able to accurately predict unplanned intubation after surgery. Further investigation is needed to assess the utility of the Unplanned Intubation Risk Index in reducing the incidence of unplanned intubation through improved risk stratification and management in perioperative care.
Disappearance and uptake of ( 125 I)FSH in the rat, rabbit, ewe and cow.

Follicle-stimulating hormone (nih-fsh-s8) was labelled with 125I to determine its disappearance rate after a single intravenous injection and to determine the level of circulating [125I]fsh in the blood after a single intramuscular or subcutaneous injection in the rat, rabbit, ewe and cow. There was a difference in the disappearance and uptake rates among the four species, but the shape of the curve for rate of loss and uptake of labelled fsh was similar in all species. The disappearance of radioactivity occurred at two rates; the first from 1 to 8 min and the second from 16 to 96 min. The half-life, calculated from the total decay
NSF: Network-Based Spam Filtering Based on On-Line Blacklisting against Spamming Botnets

Although many anti-spam techniques have been developed, they have difficulty in detecting spams whose contents are altered to evade detection and in tracking spammers that are comprised of botnets. There have been a few works to resolve these limitations, but most of them are not appropriate to be deployed at a gateway for online detection. In this paper, we find network-based characteristics that spammers cannot easily distort. Based on the characteristics, we develop an algorithm applying the metrics to a large volume of traffic in real time. The scheme is efficient enough to run at the ingress point as it only needs to inspect the transport information contained in TCP/IP headers of SMTP connections.
Small Enterprises' Predisposition to Adopt an ERP

Enterprise resource planning systems (ERPs) are now being implemented in small and medium enterprises (SMEs). In addition to allowing for the integration of technological architectures, these systems make best practices available to small firms. This paper presents the results of a study that was aimed at identifying the dimensions of SMEs’ readiness for the adoption of this new technology.
An Algorithm for Rapid Adjustment of Lower Extremity Posture of a Pedestrian Model

Posture adjustment of finite element (FE) human body model is a significant step in accident reconstruction and investigation on pedestrian kinematical and injury outcomes. A rapid posture adjustment algorithm for pedestrian lower extremities was developed to account for realistic joint kinematics during a gait cycle. Under the kinematic constraints from joint anatomy, the algorithm calculated the posture of the lower extremity at any instant of a gait cycle from the open kinematic chain linked by the hip, knee and ankle joints in sequence. Joint motions were predicted based on subject‐specific geometry, following the rules of joint motion based on the literature. Mesh morphing method were implemented to calculate nodal coordinates of soft tissues around the joints. As an application example, the proposed algorithm was exercised on the midsize male GHBMC pedestrian model and three different walking postures within a gait cycle were generated. These models were used to simulate a typical vehicle‐to‐pedestrian crash scenario. Pre‐crash posture showed significant effect on the injury risks of lower extremities, indicating necessity of taking pre‐crash postures into account for pedestrian injury investigation.