Miracle-dz/UniFAR-FTUs huggingface dataset:
Whole-exome sequencing enables correct diagnosis and surgical management of rare inherited childhood anemia

Correct diagnosis of inherited bone marrow failure syndromes is a challenge because of the significant overlap in clinical presentation of these disorders. Establishing right genetic diagnosis is crucial for patients’ optimal clinical management and family counseling. A nondysmorphic infant reported here developed severe transfusion-dependent anemia and met clinical criteria for diagnosis of Diamond–Blackfan anemia (DBA). However, whole-exome sequencing demonstrated that the child was a compound heterozygote for a paternally inherited pathogenic truncating variant (SPTA1c.4975 C>T) and a novel maternally inherited missense variant of uncertain significance (SPTA1c.5029 G>A) within the spectrin gene, consistent with hereditary hemolytic anemia due to disruption of red blood cell (RBC) cytoskeleton. Ektacytometry demonstrated abnormal membrane flexibility of the child's RBCs. Scanning electron microscopy revealed morphological aberrations of the patient's RBCs. Both parents were found to have mild hereditary elliptocytosis. Importantly, patients with severe RBC membrane defects may be successfully managed with splenectomy to minimize peripheral destruction of misshapen RBCs, whereas patients with DBA require lifelong transfusions, steroid therapy, or hematopoietic stem cell transplantation. As suggested by the WES findings, splenectomy rendered our patient transfusion-independent, improving the family's quality of life and preventing transfusion-related iron overload. This case illustrates the utility of whole-exome sequencing in clinical care of children with genetic disorders of unclear presentation.
Tracing the protective activity of Lactobacillus plantarum using technetium-99m-labeled zearalenone for organ toxicity

Abstract Purpose: Zearalenone is a potent estrogenic metabolite produced by some Fusarium and Gibberella species. Therefore, the aim of this study was to determine the accumulation of Technetium-[99m]-labeled zearalenone in mice organs as well as to study the protective effect of Lactobacillus plantarum. Materials and methods: Two different groups of mice were used; the first group of mice received Technetium-[99m]-zearalenone only, and the second group received both Technetium-[99m] zearalenone and L. plantarum (as a protective agent). Technetium-[99m]-labeled zearalenone was administered to mice by tail vein injection and L. plantarum was administered orally. Accumulation of labeled zearalenone in mice was monitored for 120 min. Results: Labeled zearalenone was distributed primarily in the intestine (44.5%) and liver (20.12%) after 120 min in the first group of mice. In the second group of mice which received both Technetium-[99m] zearalenone and L. plantarum, labeled zearalenone was accumulated primarily in the intestine (46.8%) and liver (18.9%). These results indicated the decrease in labeled zearalenone in the liver due to the effect of lactic acid bacteria. Conclusion: Technetium-[99m]-labeled zearalenone can be used as a new tracer for organ imaging and that L. plantarum can decrease the bioavailability of zearalenone in mice organs.
Run-Time Adaptive Power-Aware Reliability Management for Manycores

<italic>Editor’s note:</italic> Due to increasing process, voltage, and temperature (PVT) variability, reliability is becoming a growing worry. This article addresses this concern with a combination of software and hardware hardening modes while considering power, performance, and overhead constraints. Similar to other examples in this special issue, this work illustrates that complex management tasks that have to integrate multiple objectives, goals, and constraints require a comprehensive understanding of the system’s state. <italic>—Axel Jantsch, TU Wien</italic> —<italic>Nikil Dutt, University of California at Irvine</italic>
The cerebral circulation: The centrality of its function, the catastrophe of its failure

A the brain may contribute only a modest 2% to the body’s total mass, it uses a wildly disproportionate 25% of the body’s total glucose utilization, and 15%–20% of its total cardiac output. [1,2] This disproportionality may be striking, but it is wholly in keeping with the power and importance of the myriad functions underwritten by the brain. Many of these functions are indispensable to survival, such as the respiratory and cardiac rhythms controlled by the autonomic centers in the brainstem, the sleep and feeding cycles regulated by the hypothalamus, and the sensory modalities with which we find nutrients and avoid dangers presented by our environment. Many other cerebral functions, while not strictly necessary for survival, are nevertheless numbered among life’s preeminent treasures: the capacity to design cities, to compose symphonies, to communicate one’s inner life through language to loved ones.
Content Based Image Retrieval Using Multi-Sequential Search

In Content-Based Image Retrieval (CBIR) the indexing of the image and the representation is done using visual contents of an image like color, shape, texture and spatial layout. The on-going development and research in CBIR are mainly focused on the improvement of various methods for examining, cataloging and indexing image databases. Along with this development, several efforts are also being made in evaluating the performance of the image retrieval systems. Depending on the method incorporated to generate the similarity measure for the comparisons of different features and the vectors the accuracy and response of the system would vary. The proposed system is exclusive as it takes into consideration one particular feature at one step and uses the result of the above prior step as the input for the next step instead of fusing all the features at one step and thus providing an edge over the earlier used methods and also showing improvement in the retrieval quality. In the proposed system the accuracy of color histogram-based matching can be increased by using Color Coherence Vector. Instead of taking into consideration the exact shape, the approximation of the boundary is considered in order to enhance the speed of shape-based matching.
Influence of peer networks on physician adoption of new drugs

Although physicians learn about new medical technologies from their peers, the magnitude and source of peer influence is unknown. We estimate the effect of peer adoption of three first-in-class medications (dabigatran, sitigliptin, and aliskiren) on physicians’ own adoption of those medications. We included 11,958 physicians in Pennsylvania prescribing anticoagulant, antidiabetic, and antihypertensive medications. We constructed 4 types of peer networks based on shared Medicare and Medicaid patients, medical group affiliation, hospital affiliation, and medical school/residency training. Instrumental variables analysis was used to estimate the causal effect of peer adoption (fraction of peers in each network adopting the new drug) on physician adoption (prescribing at least the median number prescriptions within 15 months of the new drug’s introduction). We illustrate how physician network position can inform targeting of interventions to physicians by computing a social multiplier. Dabigatran was adopted by 25.2%, sitagliptin by 24.5% and aliskiren by 8.3% of physicians. A 10-percentage point increase in peer adoption in the patient-sharing network led to a 5.90% (SE = 1.50%, p<0.001) increase in physician adoption of dabigatran, 8.32% (SE = 1.51%, p<0.001) increase in sitagliptin, and 7.84% increase in aliskiren adoption (SE = 2.93%, p<0.001). Peer effects through shared hospital affiliation were positive but not significant, and medical group and training network effects were not reliably estimated. Physicians in the top decile of patient-sharing network peers were estimated to have nearly 2-fold stronger influence on their peers’ adoption compared to physicians in the top decile of prescribing volume. Limitations include lack of detailed clinical information and pharmaceutical promotion, variables which may influence physician adoption but which are unlikely to bias our peer effect estimates. Peer adoption, especially by those with whom physicians share patients, strongly influenced physician adoption of new drugs. Our study shows the potential for using information on physician peer networks to improve technology diffusion.
Understanding the impact of video quality on user engagement

As the distribution of video over the Internet is becoming mainstream, user expectation for high quality is constantly increasing. In this context, it is crucial for content providers to understand if and how video quality affects user engagement and how to best invest their resources to optimize video quality. This paper is a first step toward addressing these questions. We use a unique dataset that spans different content types, including short video on demand (VoD), long VoD, and live content from popular video content providers. Using client-side instrumentation, we measure quality metrics such as the join time, buffering ratio, average bitrate, rendering quality, and rate of buffering events. We find that the percentage of time spent in buffering (buffering ratio) has the largest impact on the user engagement across all types of content. However, the magnitude of this impact depends on the content type, with live content being the most impacted. For example, a 1% increase in buffering ratio can reduce user engagement by more than 3 min for a 90-min live video event.
Hybrid Static-Dynamic Modeling and Experimental Analysis of Multi-Scale Complex Environments: Application to Ubiquitous Interactions

Hybridization of agile mm-Wave MIMO and Phased-Array technologies with static (Capacitive-Resistive-Inductive effects) and dynamic multi-physics (coupled ultrasonic and optical waves) sensing solutions is proposed toward new functionalities for environmental perceptions and ubiquitous interactions. The resulting paradigms will operate the unification of Contact-driven actions and contactless Gesture-driven interactions for enabling emerging technologies relative to interactions of humans with smart devices and systems in randomly changing environments. Perspectives for Autonomous Vehicles with Advanced Driver Assistance Systems (ADAS) including Gesture-Recognition (GR) through ubiquitous interactions based on hybrid agile mm-Wave RFIC technologies and optical systems are drawn.
Group-Level Emotion Recognition using Deep Models with A Four-stream Hybrid Network

Group-level Emotion Recognition (GER) in the wild is a challenging task gaining lots of attention. Most recent works utilized two channels of information, a channel involving only faces and a channel containing the whole image, to solve this problem. However, modeling the relationship between faces and scene in a global image remains challenging. In this paper, we proposed a novel face-location aware global network, capturing the face location information in the form of an attention heatmap to better model such relationships. We also proposed a multi-scale face network to infer the group-level emotion from individual faces, which explicitly handles high variance in image and face size, as images in the wild are collected from different sources with different resolutions. In addition, a global blurred stream was developed to explicitly learn and extract the scene-only features. Finally, we proposed a four-stream hybrid network, consisting of the face-location aware global stream, the multi-scale face stream, a global blurred stream, and a global stream, to address the GER task, and showed the effectiveness of our method in GER sub-challenge, a part of the six Emotion Recognition in the Wild (EmotiW 2018) [10] Challenge. The proposed method achieved 65.59% and 78.39% accuracy on the testing and validation sets, respectively, and is ranked the third place on the leaderboard.
Intelligent Irrigation System based on Wireless Sensor Networks

India, being a developing nation, basically relies on farming. For farming water is essential factor. In other countries also the major profession of human Being is agriculture, out of available land 64% is engaged by the farming, and it needs nearly 85% of clean water. This paper represents the irrigation system using the Linux board and wireless sensor network. Fundamentally, it includes two nodes which are named as Coordinator node which will be at receiver side and Sensor node which will be at transmitter side. Two parameters of the soil that is temperature of soil and moisture of soil are used for the decision to make either Irrigation turned on or off. In this proposed system, Raspberry Pi 3 is used as a coordinator node which collects the data collected by the sensors. RPi communicates with the sensor node uses ZigBee wireless protocol for communication. Web server will be designed at the Raspberry Pi through which user can control the level of water depending on the values of temperature and moisture remotely.
Beyond Rail-to-Rail Compliant Current Sources for Mismatch-Insensitive Voltage-to-Time Conversion

This brief presents beyond rail-to-rail (BR2R) compliant cascode current sources to markedly improve the compliance voltage and output impedance of the extensively used wide-swing cascode current source. The proposed BR2R sources employ a bootstrapping technique to linearly charge a load capacitor to beyond the supply rails <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ dd}}$ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">$gnd$ </tex-math></inline-formula> while maintaining an improved output impedance over an equivalent wide-swing cascode source. A process and mismatch-insensitive differential voltage-to-time (DVT) converter employing these BR2R sources is fabricated in 65-nm CMOS and occupies <inline-formula> <tex-math notation="LaTeX">$0.021~\text {mm}^{2}$ </tex-math></inline-formula>, while dissipating <inline-formula> <tex-math notation="LaTeX">$47~\mu \text{W}$ </tex-math></inline-formula> at 1 V. The measured BR2R DVT signal to noise and distortion ratio is 50.2 dB, compared to 38.7 dB for the wide-swing cascode-based DVT within a 2-MHz input bandwidth. The DVT achieves a common mode rejection ratio of 35.1 dB for a 0.4–0.6-V input common-mode range.
A Roadmap towards Tuneable Random Ontology Generation Via Probabilistic Generative Models

: As the sophistication of the tools available for manipulating ontologies increases, so does the need for novel and rich ontologies to use for purposes such as benchmarking, testing and validation. Ontology repositories are not ideally suited for this need, as the ontologies they contain are limited in number, may not generally have required properties (e.g., inconsistency), and may present unwelcome correlations between features. In order to better match this need, we hold that a highly tuneable, language-agnostic, theoretically principled tool for the automated generation of random ontologies is needed. In this position paper we describe how a probabilistic generative model (based on features obtained via the analysis of real ontologies) should be developed for use as the theoretical back-end for such an enterprise, and discuss the role of the DOL metalanguage in it.
Tattoo Recognition in Screening for Victims of Human Trafficking

Abstract There is little information on the secondary prevention of human trafficking and how medical professionals can screen for victims. There is a paucity of validated screening tools for use in clinical settings to identify adult trafficked patients, although one for use in pediatric populations exists. Many victims withhold information about their trafficked status. Because traffickers may mark victims, identification of tattoos provides a useful method for screening patients, which complements history taking, especially when victims are unable to disclose that information. We searched existing medical literature, PsycINFO, PubMed, Google, and JSTOR using keywords “human,” “trafficking,” and “tattoos. ” Because there is scant literature on this topic, we also searched the gray literature that enabled preliminary identification of several themes used in trafficking tattoos. We also discussed tattoo placement and quality. Tattoo recognition is a critical factor in identifying victims and setting them on a pathway to freedom and recovery.
Rotationally-Invariant Multi-Dimensional Trellis Coded Modulation for Optical Transmission Systems

We review the principle of multidimensional (multi-D) trellis coded modulation (TCM). We describe the structure of multi-D TCM schemes and discuss their main advantages. Numerical simulations show that multi-D TCM combined with simple hard-decision forward error correction (HD-FEC) codes are of practical interest, as they can provide a better trade-off between complexity and performance, compared to soft-decision (SD-)FEC alternatives. Moreover, the scheme is resilient to cycle-slip events due to its 90° phase rotation-invariant property.
Homogeneous Green's Function Retrieval on Field Data Using the Marchenko Method

Retrieval of the homogeneous Green's function is often done using a single-sided boundary, even though the theory states that an enclosing boundary is required. In recent years the theory has been modified to create a single-sided representation. This is done by using the Marchenko method, to redatum the wavefield from the boundary to a virtual receiver location inside the medium. The results on synthetic data have been encouraging, but on field data this method is largely unproven, due to the fact that the Marchenko method assumes that the medium is lossless, which in practice it is not. We have shown how to apply the classical representation and that it does not deliver the desired result on the field data. We have also demonstrated how to apply the new representation on the field data and that the result has improved over the classical representation. We visualize the result as snapshots over a region of interest to show the propagation of the wavefield through the medium.
Increased Activity Due to Fractures Does Not Significantly Affect the Accuracy of 68Ga-DOTATATE PET/CT in the Detection of Culprit Tumor in the Evaluation of Tumor-Induced Osteomalacia

Objective 68Ga-DOTATATE PET/CT is currently the most common imaging modality in localizing culprit tumors, which can result in tumor-induced osteomalacia (TIO). Fracture, which is one of the most common consequences of the TIO, can also lead to increased 68Ga-DOTATATE activity and potentially affect the accuracy of 68Ga-DOTATATE PET/CT imaging. The aim of this investigation is to evaluate whether the increased 68Ga-DOTATATE activity at the sites of the fracture will cause interpretation difficulty in the localizing the culprit tumor causing TIO. Method The images of 68Ga-DOTATATE PET/CT scan from a total of 54 patients who had multiple foci of increased 68Ga-DOTATATE PET/CT on PET/CT were retrospectively analyzed. Not only was the intensity of the activity on PET but also the appearance of the activity on CT taken into consideration when the interpretation of the images occurred. The results from imaging analysis were compared with the clinical chart record. All patients had tentative clinical diagnosis of TIO. Results The causative tumors in 53 patients were eventually identified. In 1 patient, the causative tumor was not identified. Among the 53 patients with confirmed TIO, 52 tumors were accurately localized. Conclusions Mild activity at the sites of fracture is not a major challenging factor in the interpretation of 68Ga-DOTATATE PET/CT in the evaluation of TIO when both intensity on PET and morphology on CT were assessed.
Wibheda+: Framework for Data Dependency-aware Multi-constrained Hardware-Software Partitioning in FPGA-based SoCs for IoT Applications

FPGA-based system-on-chip (SoC) devices for Internet of Things (IoT) applications require hardware-software (HW-SW) partitioning techniques to optimize for performance under stringent area and power constraints. To obtain an optimally partitioned design it is necessary to account for the data communication cost between hardware and software. However, the large design space during partitioning makes it challenging to account for this cost while optimizing for stringent constraints using an exhaustive approach. Hence, we propose Wibheda+, a heuristic based framework for fine-grained data dependency-aware multi-constrained HW-SW partitioning that can be employed to partition designs for FPGA-based SoCs used in IoT. Wibheda+, evaluated on 10 applications from the CHStone benchmark suite, has been shown to find solutions with 99% accuracy within several milliseconds compared to several minutes or hours taken in a state-of-the-art and an exhaustive approach, respectively.
An Artificial Bee Colony-Based Green Routing Mechanism in WBANs for Sensor-Based E-Healthcare Systems

At present, sensor-based E-Healthcare systems are attracting more and more attention from academia and industry. E-Healthcare systems are usually a Wireless Body Area Network (WBANs), which can monitor or diagnose human health by placing miniaturized, low-power sensor nodes in or on patient’s bodies to measure various physiological parameters. However, in this process, WBAN nodes usually use batteries, and especially for implantable flexible nodes, it is difficult to accomplish the battery replacement, so the energy that the node can carry is very limited, making the efficient use of energy the most important problem to consider when designing WBAN routing algorithms. By considering factors such as residual energy of node, the importance level of nodes, path cost and path energy difference ratios, this paper gives a definition of Optimal Path of Energy Consumption (OPEC) in WBANs, and designs the Optimal Energy Consumption routing based on Artificial Bee Colony (ABC) for WBANs (OEABC). A performance simulation is carried out to verify the effectiveness of the OEABC. Simulation results demonstrate that compared with the genetic algorithm and ant colony algorithm, the proposed OEABC has a better energy efficiency and faster convergence rate.
Discrete-Time Control Design for Three-Phase Grid-Connected Inverter Using Full State Observer

LCL filters are being more and more preferred over the L filter in a grid-connected inverter due to the smaller physical size and better harmonic attenuation characteristics. However, additional control loops are often required to control inverter-side current as well as capacitor voltage. These additional control loops complicate the controller design process. To overcome such a limitation, a discrete-time control design for a three-phase grid-connected inverter using a full state observer is presented in this paper. The controller design is accomplished based on the state-space model of the inverter system. Furthermore, to reduce the steady-state error in output currents, a discrete-time integral state feedback controller is employed. Generally, all state variables should be available to implement a state feedback controller. For the purpose of reducing the number of sensors in a practical system, an observer which uses the measured grid-side currents, grid voltages, and control inputs is constructed in discrete-time domain to predict the inverter-side currents and capacitor voltages. As a result of using both the feedback controller and the observer, the proposed control scheme provides a better control performance in a systematic design approach. Simulation results are given to demonstrate the feasibility and performance of the proposed control scheme.