Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparing for a Foreign Animal Disease Outbreak Using a Novel Tabletop Exercise

Abstract Introduction Foreign animal disease (FAD) outbreaks can have devastating impacts, but they occur infrequently in any specific sector anywhere in the United States (US). Training to proactively discuss implementation of control and prevention strategies are beneficial in that they provide stakeholders with the practical information and educational experience they will need to respond effectively to an FAD. Such proactive approaches are the mission of the Secure Food System (SFS; University of Minnesota; St. Paul, Minnesota USA). Methods The SFS exercises were designed as educational activities based on avian influenza (AI) outbreaks in commercial poultry scenarios. These scenarios were created by subject matter experts and were based on epidemiology reports, risk pathway analyses, local industry practices, and site-specific circumstances. Target audiences of an exercise were the groups involved in FAD control: animal agriculture industry members; animal health regulators; and diagnosticians. Groups of industry participants seated together at tables represented fictional poultry premises and were guided by a moderator to respond to an on-farm situation within a simulated outbreak. The impact of SFS exercises was evaluated through interviews with randomized industry participants and selected table moderators. Descriptive statistics and qualitative analyses were performed on interview feedback. Results Eleven SFS exercises occurred from December 2016 through October 2017 in multiple regions of the US. Exercises were conducted as company-wide, state-wide, or regional trainings. Nine were based on highly pathogenic avian influenza (HPAI) outbreaks and two focused on outbreaks of co-circulating HPAI and low pathogenicity avian influenza (LPAI). Poultry industry participants interviewed generally found attending an SFS exercise to be useful. The most commonly identified benefits of participation were its value to people without prior outbreak experience and knowledge gained about Continuity of Business (COB)-permitted movement. After completing an exercise, most participants evaluated their preparedness to respond to an outbreak as somewhat to very ready, and more than one-half reported their respective company or farms had discussions or changed actions due to participation. Conclusion: Evaluation feedback suggests the SFS exercises were an effective training method to supplement preparedness efforts for an AI outbreak. The concept of using multi-faceted scenarios and multiple education strategies during a tabletop exercise may be translatable to other emergency preparedness needs. LinskensEJ, NeuAE, WalzEJ, St. CharlesKM, CulhaneMR, SsematimbaA, GoldsmithTJ, HalvorsonDA, CardonaCJ. Preparing for a foreign animal disease outbreak using a novel tabletop exercise. Prehosp Disaster Med. 2018;33(6):640–646.
Acoustic Modeling from Frequency Domain Representations of Speech

In recent years, different studies have proposed new methods for DNN-based feature extraction and joint acoustic model training and feature learning from raw waveform for large vocabulary speech recognition. However, conventional pre-processed methods such as MFCC and PLP are still preferred in the state-of-the-art speech recognition systems as they are perceived to be more robust. Besides, the raw waveform methods – most of which are based on the time-domain signal – do not signiﬁ-cantly outperform the conventional methods. In this paper, we propose a frequency-domain feature-learning layer which can allow acoustic model training directly from the waveform. The main distinctions from previous works are a new normalization block and a short-range constraint on the ﬁlter weights. The proposed setup achieves consistent performance improvements compared to the baseline MFCC and log-Mel features as well as other proposed time and frequency domain setups on different LVCSR tasks. Finally, based on the learned ﬁlters in our feature-learning layer, we propose a new set of analytic ﬁlters using polynomial approximation, which outperforms log-Mel ﬁlters signiﬁcantly while being equally fast.
Alternative treatment strategies to sorafenib in patients with advanced hepatocellular carcinoma: a meta-analysis of randomized Phase III trials

Introduction This meta-analysis was conducted to evaluate efficacy and safety in patients treated with sorafenib vs other tyrosine-kinase inhibitors (TKIs) or selective internal radiotherapy (SIRT) for advanced hepatocellular carcinoma (HCC). Methods Electronic databases were systematically reviewed for randomized Phase III trials comparing sorafenib with other TKIs or SIRT in advanced HCC. Sorafenib was defined as the control arm. Other TKIs or SIRT was defined as the experimental arm. Overall survival (OS), time to progression (TTP), objective response rate (ORR), disease-control rate (DCR), and adverse events (AEs) were reviewed. Four trials in the other-TKI group (n=4,218) and two in the SIRT group (n=819) were eligible. Results Compared with sorafenib, other TKIs showed similar benefit on OS (HR 1.08, 95% CI 0.93–1.24; P=0.31) and TTP (HR 0.86, 95% CI 0.66–1.12; P=0.26) for advanced HCC. A significant increase in ORR (RR 1.67, 95% CI 1.15–2.43; P=0.008) was found with other TKIs, but no increase in DCR (RR 1.11, 95% CI 0.98–1.26; P=0.11) was observed. Other TKIs were associated with more frequent grade 3/4 AEs than sorafenib, including hypertension (P<0.00001), thrombocytopenia (P=0.002), fatigue (P<0.00001), decreased appetite (P<0.00001), and vomiting (P<0.0001). For locally advanced HCC, neither OS (HR 1.14, 95% CI 0.98–1.32; P=0.09) nor TTP (HR 0.87, 95% CI 0.74–1.02; P=0.10) differed significantly in SIRT and sorafenib. There was an increase in ORR (RR 2.60, 95% CI 1.69–4.00; P<0.0001), but no improvement in DCR (RR 0.91, 95% CI 0.81–1.02; P=0.11) in the SIRT group. Fewer patients treated with SIRT had grade 3/4 AEs than those treated with sorafenib, including diarrhea (P<0.0001), fatigue (P=0.0006), and hand–foot syndrome (P=0.0002). Other TKIs were noninferior to sorafenib in OS and TTP in advanced HCC, but with increased risk of toxicities. Conclusion Patients with locally advanced HCC treated with SIRT got similar efficacy with less toxicity to those treated with sorafenib.
Highly Substituted Benzophenone Aldehydes and Eremophilane Derivatives from the Deep-Sea Derived Fungus Phomopsis lithocarpus FS508

Five new benzophenone derivatives named tenellones D–H (1–5), sharing a rare naturally occurring aldehyde functionality in this family, and a new eremophilane derivative named lithocarin A (7), together with two known compounds (6 and 8), were isolated from the deep marine sediment-derived fungus Phomopsis lithocarpus FS508. All of the structures for these new compounds were fully characterized and established on the basis of extensive spectroscopic interpretation and X-ray crystallographic analysis. Compound 5 exhibited cytotoxic activity against HepG-2 and A549 cell lines with IC50 values of 16.0 and 17.6 μM, respectively.
RF MEMS Based 60 GHz Variable Attenuator

This paper presents a millimeter-wave variableattenuator realized using a lateral radio-frequency (RF) microelectromechanical systems (MEMS) capacitive type switch. The proposed variable attenuator comprises of two CPW based quadrature hybrid couplers paired with capacitive type thermally-actuated lateral MEMS switches. The voltage applied to the Chevron actuator regulates the precise mechanical movement of the contact plate and hence defines the range of attenuation. At the center frequency of 60 GHz, the attenuation monotonically varied from 4 dB to 20 dB with the applied voltage. Return loss better than 20 dB over a bandwidth of 4 GHz is achieved. The proposed fabrication process provides the ability to integrate the lateral actuators, movable plates, RF CPW lines, and the CPW hybrid coupler and other supporting structures on an SOI substrate.
Distributed Finite Time Consensus of Second-Order Multi-Agent Systems via Pinning Control (August 2018)

The robust distributed finite time consensus of second-order multi-agent systems via pinning control has been investigated in this paper. A new nonsingular finite time terminal sliding-mode control method is proposed for second-order single system with disturbances. Based on the pinning error function vector, robust distributed finite time consensus of second-order multi-agent systems via pinning control method is given. Simulations results are performed to validate the effectiveness of the theoretical results.
Surface Flows From Magnetograms

Estimates of velocities from time series of photospheric and/or chromospheric vector magnetograms can be used to determine fluxes of magnetic energy (the Poynting flux) and helicity across the magnetogram layer, and to provide time-dependent boundary conditions for data-driven simulations of the solar atmosphere above this layer. Velocity components perpendicular to the magnetic field are necessary both to compute these transport rates and to derive model boundary conditions. Here, we discuss some possible approaches to estimating perpendicular flows from magnetograms. Since Doppler shifts contain contributions from flows parallel to the magnetic field, perpendicular velocities are not generally recoverable from Doppler shifts alone. The induction equation's vertical component relates evolution in $B_z$ to the perpendicular flow field, but has a finite null space, meaning some ``null'' flows, e.g., motions along contours of normal field, do not affect $B_z$. Consequently, additional information is required to accurately specify the perpendicular flow field. Tracking methods, which analyze $\partial_t B_z$ in a neighborhood, have a long heritage, but other approaches have recently been developed. In a recent paper, several such techniques were tested using synthetic magnetograms from MHD simulations. Here, we use the same test data to characterize: 1) the ability of the induction equation's normal component, by itself, to estimate flows; and 2) a tracking method's ability to recover flow components that are perpendicular to $\mathbf{B}$ and parallel to contours of $B_z$. This work has been supported by NASA Heliophysics Theory grant NNG05G144G.
Reputation-Aware Trust and Privacy-Preservation for Mobile Cloud Computing

Mobile Cloud Computing (MCC) is getting growing interest due to its wide applicability in variety of social, industrial, and commercial mobile applications. Mobile and smart devices can share complex computational operations with Cloud Service Providers (CSPs). It also provides storage, access polices enforcement, and security operations. In many cases, CSP requires services from crowd contributors CCs for data collection, sharing, and mobile application support. It requires trust management for CCs to guard against malicious CCs and ensure security and privacy of data. However, end users or data requesters also demand reliable security solutions for sharing their data or accessing data from unknown CCs. To ensure strong security, mobile devices are not computationally feasible to perform complex cryptographic operations for desired privacy. To resolve these issues, we propose Reputation-aware Trust and Privacy Preservation scheme for MCC. In first phase, we deal with the trust management by utilizing reputation aware selection of CCs and leverage cloud services where CSP maintains trust score for CCs and data requesters. In second phase, we manage privacy preservation by using our proposed Anonymous Secure-shell Ciphertext-policy Attribute Based Encryption (AS-CABE). We have also proposed a hybrid policy tree mechanism for dynamic attribute selection used for security solutions and key management. Next, an anonymous secure shell is maintained between the CCs and the crowd servers to ensure registration after approval from trusted authority. In the similar vein, we propose outsourced encryption and decryption mechanism for mobiles that further utilize encryption and decryption service providers for complex operations. To the best of our knowledge, we are the first one to deal with the trust issues of data requester and privacy concerns of CCs and users both at the same time. After that, we have presented the security analysis to analyze AS-CABE against security attacks. Finally, the results are presented that ensure the supremacy of our proposed scheme as compared to counterparts in terms of reputation score, storage, computation, trust, resilience, encryption, and decryption time.
FocusAR: Auto-focus Augmented Reality Eyeglasses for both Real World and Virtual Imagery

We describe a system which corrects dynamically for the focus of the real world surrounding the near-eye display of the user and simultaneously the internal display for augmented synthetic imagery, with an aim of completely replacing the user prescription eyeglasses. The ability to adjust focus for both real and virtual stimuli will be useful for a wide variety of users, but especially for users over 40 years of age who have limited accommodation range. Our proposed solution employs a tunable-focus lens for dynamic prescription vision correction, and a varifocal internal display for setting the virtual imagery at appropriate spatially registered depths. We also demonstrate a proof of concept prototype to verify our design and discuss the challenges to building an auto-focus augmented reality eyeglasses for both real and virtual.
Cloud Workflow Resource Shortage Prediction and Fulfillment Using Multiple Adaptation Strategies

Extending workflow orchestration to embrace monitoring and adaptation within cloud environment is perceived to be a challenging activity. It has to consider different resources, require heavy processing to adapt to the dynamic nature of cloud environment. In this paper, we propose a multi-model framework for workflow resource monitoring, prediction, and adaptation. The framework supports continuous monitoring of several workflow runtime cloud entities and detect diverse types of violations (e.g. resource saturation). Moreover, collected logs resulted from monitoring are used as a training dataset for predicting resource shortage. Furthermore, two adaptation strategies are proposed to cope with environment resources changes and avoid violations: 1) monitoring-based adaptation and 2) prediction-based adaptation. Both adaptation schemes perform the necessary actions to adapt resources according to workflow required quality levels. To evaluate our monitoring and adaptation approaches we used a real cloud environment where we perform a couple of experimental scenarios. Experiments results showed that our framework and proposed monitoring, prediction and adaptation schemes are efficient in detecting violations, accurately predicting cloud resource shortages and accordingly issuing the proper adapting decisions.
Using Wikipedia to Enable Entity Retrieval and Visualization Concerning the Intellectual/Cultural Heritage

At the 2009 Digital Humanities conference I presented my paper on the WikiPhiloSofia (http://research.cis.drexel.e du:8080/sofia/WPS/) project (Athenikos and Lin, 2009), which was concerned with extraction and visualization of facts, relations, and networks concerning philosophers using Wikipedia (http://www.wikipedia.org/) as the data source. In this proposal, I present a related, extended project in progress, entitled PanAnthropon, which incorporates the problems of retrieving entities in response to a query and retrieving entities related to a given entity and which extends the scope of application to domains other than philosophy.
Silhouette Enhancement in Light Field Disparity Estimation Using the Structure Tensor

This paper presents a method to improve disparity maps computed from light field images using structure tensor methods, which tend to expand the borders of the occluding objects, enlarging their silhouette. The proposed method relies on the fact that such regions of the silhouette are defined by a mismatch between the disparity map edges, computed by the structure tensor, and those of the corresponding epipolar plane images (EPI) representing the light field. The proposed silhouette improvement method determines a correspondence between EPI edges and the disparity map edges, identifying the erroneous silhouette regions. The disparity map is corrected by using neighbouring values computed with high structure tensor reliability. The achieved results show that the disparity map is improved both around object edges and overall, reducing the MSE by 47.9% in comparison with other methods also based on the structure tensor.
An Adaptive Particle Swarm Optimization for Underwater Target Tracking in Forward Looking Sonar Image Sequences

In order to obtain accurate underwater target tracking results in forward-looking sonar image sequences, an adaptive particle swarm optimization (APSO) algorithm is proposed to track the underwater target. Specifically, an adaptive inertia weight is first applied to solve the problem of diversity loss and premature convergence in the PSO algorithm. Then, the individual optimal fitness value of a random particle selected from particle swarm is compared with that of the current particle, and the larger one is used to update the velocity of the particle to further prevent particles from falling into the local optimum. On this basis, when the underwater target is occluded, a new update strategy based on an adaptive discrete swarm optimization algorithm is used to update the particle’s position according to the level of occlusion so as to achieve a better tracking result. Finally, the experimental results show that the proposed APSO can accurately complete underwater target tracking. Compared with other algorithms, the proposed APSO has higher tracking accuracy and faster tracking speed, and it has a certain effectiveness and adaptability.
Closed-Form Approximation of LoRa Modulation BER Performance

LoRa has been demonstrated as a front runner when it comes to evolving low-power wide area networks. At its core is LoRa modulation which depicts a patented chirp spread-spectrum modulation technique that supports energy-efficient and reliable long-range communication. The underlying bit error rate (BER) performance of LoRa modulation has not been yet rigorously analyzed in the literature. In this letter, closed-form approximations for LoRa BER performance are derived for both additive white Gaussian noise and Rayleigh fading channels. Accuracy of the derived approximations is confirmed by comparisons against numerical results.
The Efficacy and Safety of Enoxaparin: A Meta-analysis

Abstract The efficacy and safety of enoxaparin (ENOX) in percutaneous coronary intervention (PCI) for ST-elevation myocardial infarction (STEMI) remains unaddressed. The primary endpoint evaluated was myocardial infarction (MI) or death. The secondary endpoint was defined as major bleeding complications. Studies comparing the differences in the efficacy and safety of ENOX versus unfractionated heparin (UFH) in PCI for the treatment of STEMI were evaluated. We presented the odds ratios for individual studies and performed heterogeneity, quality assessment, and publication bias analysis. This meta-analysis examined four randomized controlled trials (RCTs), and 5585 patients were included (2334 ENOX patients and 3251 UFH patients). The follow-up period of the endpoints was 30 or 90 days. Compared with UFH, ENOX significantly reduced the incidence of MI (OR, 0.74; P<0.01) and death (OR, 0.74; P<0.03), while there was no significant difference between the two treatments on major bleeding (OR,0.81; P=0.33). The findings from this meta-analysis suggested that the efficacy and safety of ENOX in the treatment of STEMI patients undergoing PCI were significantly better than patients treated with UFH. According to this meta-analysis, ENOX is the preferred anticoagulant for STEMI patients receiving PCI compared to UFH.
Angle of Arrival-Based Cooperative Positioning for Smart Vehicles

The limited localization capabilities provided by global navigation satellite systems (GNSS) is one of the main obstacles toward the development of reliable road safety applications in urban scenarios. In order to improve GNSS accuracy, a number of approaches have been proposed which exploit additional position-related information, for instance provided by local inertial sensors. However, such solutions cannot meet the very stringent accuracy requirements of safety applications, which call for advanced processing and the fusion of position-related signals and data from heterogeneous sources. In this paper, we aim at combining the potential of antenna array processing with a suitably-designed cooperation strategy that exploits vehicle-to-vehicle and vehicle-to-infrastructure communications. Particularly, we define a novel tracking algorithm with asynchronous updates triggered by beacon packet receptions, from which angle of arrival estimates are opportunistically obtained. A dynamic setting of relevant parameters allows the resulting cooperative positioning algorithm to adapt to the different operating conditions found in urban vehicular contexts. Simulation results under realistic environment conditions show that the proposed algorithm can achieve high position accuracy even in sparse scenarios, outperforming a natural competitor while keeping lightweight communication and low computational complexity.
Proteomic Profiling of Native Unpassaged and Culture‐Expanded Mesenchymal Stromal Cells (MSC)

Human culture‐expanded mesenchymal stromal cells (MSC) are being considered for multiple therapeutic applications because of their regenerative and anti‐inflammatory properties. Although a large number of MSC can be propagated from a small initial sample, several lines of evidence indicate that MSC lose their immunosuppressive and regenerative potency aftaer multiple passages. In this report, we use the FACSCAP Lyoplate proteomic analysis system to detect changes in cell surface protein expression of CD45−/CD31−/CD34−/CD73+/CD105+ stromal cells in unpassaged bone marrow (BM) and through 10 serial culture passages. We provide for the first time a detailed characterization of native unpassaged BM MSC (0.08% of BM mononuclear cells) as well as the changes that occur during the initial expansion. Adipogenic and osteogenic differentiative potential was determined though the serial passages and correlated with immunophenotypic changes and senescence. Among the most prominent were striking decreases in Fas ligand, CD98, CD205, and CD106, accompanied by a gain in the expression of CD49c, CD63, CD98, and class 1 and class 2 major histocompatibility complex (MHC) molecules. Other molecules that are down‐modulated with later passage include CD24, CD54, CD59, CD243/P‐glycoprotein, and CD273/PD‐L2. Early senescence, as defined by the loss of replicative capacity occurring with the loss of differentiative capacity, increase in CDKN2A p16, and increased time to confluence, was accompanied by loss of the motility‐associated metalloproteinase CD10 and the proliferation‐associated transferrin receptor CD71. Among the strongest statistical associations were loss of MAC‐inhibitory protein/CD59, loss of ICAM‐1/CD54, and increase in CDKN2A as a function of increasing passage, as well as increased CD10 expression with adipogenic and osteogenic capacities. The data provide a clear set of markers that can be used to assess MSC quality. We suggest that clinically relevant numbers of highly functional low passage MSC can be manufactured starting with large quantities of BM, which are readily available from cadaveric organ donors.