Miracle-dz/UniFAR-FTUs huggingface dataset:
Feasibility of Infrarenal Abdominal Aorta Balloon Occlusion in Pernicious Placenta Previa Coexisting with Placenta Accrete

Objective To evaluate the efficacy and safety of prophylactic balloon occlusion of the infrarenal abdominal aorta in pernicious placenta previa coexisting with placenta accrete. Methods This retrospective study was performed in patients with placenta accreta complicated with pernicious placenta previa between January 2014 and December 2016 in Shengjing Hospital; 56 patients with a pathological diagnosis were included. The degree of placental invasion was evaluated by preoperative color Doppler ultrasonography and/or magnetic resonance imaging, and all patients in this study should undergo balloon occlusion preoperatively, which was a determination made by specific doctors. The control group consisted of 32 patients who underwent cesarean section alone, and the study group included 24 patients who underwent cesarean section with preoperative balloon occlusion. Prevention of hysterectomy was the primary outcome evaluated. The secondary outcomes include operative duration, estimated blood loss, blood transfusion, prothrombin time postoperatively, decrease in the hemoglobin level postoperatively, intensive care unit admission, pathological diagnosis, and total hospital stay (days), and these data were compared between the two groups. Additionally, the neonatal outcomes, premature delivery, Apgar scores at 1 minute and 5 minutes, neonatal birth weight, hospitalization, and mortality were compared. Results There was a significant difference in the rate of hysterectomy between the two groups (p<0.05). However, no differences were observed between the groups in any other outcomes. Conclusion The prophylactic use of infrarenal abdominal aortic balloon occlusion is an effective and safe option for treating pernicious placenta previa coexisting with placenta accreta.
Detection and Analysis of Content Creator Collaborations in YouTube Videos using Face- and Speaker-Recognition

This work discusses and implements the application of speaker recognition for the detection of collaborations in YouTube videos. CATANA, an existing framework for detection and analysis of YouTube collaborations, is utilizing face recognition for the detection of collaborators, which naturally performs poor on video-content without appearing faces. This work proposes an extension of CATANA using active speaker detection and speaker recognition to improve the detection accuracy.
Fast local binary pattern: Application to document image retrieval

The volume of digitised documents is increasing every day. Thus, designing a fast document image retrieval method for the large volume of document images, especially when the document images are also large in size, is of high demand. As feature extraction is one of the important steps in every document image retrieval system, a feature extraction technique with a low computing time and small feature number has a direct effect on the speed of the retrieval system. In this paper, we propose a non-parametric texture feature extraction method based on summarising the local grey-level structure of the image. To extract the proposed features, the input image is, at first, divided into a set of overlapping patches of equal size. The peripheral pixels of the centre pixel in a patch are used to extract two sets of patterns. The patterns are derived from the vertical & horizontal, and diagonal & off-diagonal pixels of the patch, separately. From each set of pixels, 15 different local binary patterns are extracted in our proposed feature extraction method. Two histograms of the local binary patterns are then created and concatenated to obtain 30 features called fast local binary pattern (F-LBP). To evaluate the efficiency of the proposed feature extraction method, MTDB and ITESOFT databases were considered for experimentation. The proposed F-LBP provided promising results with lower computing time as well as smaller memory space consumption compared to other variation of LBP methods.
Expressivity in Natural and Artificial Systems

Roboticists are trying to replicate animal behavior in artificial systems. Yet, quantitative bounds on capacity of a moving platform (natural or artificial) to express information in the environment are not known. This paper presents a measure for the capacity of motion complexity -- the expressivity -- of articulated platforms (both natural and artificial) and shows that this measure is stagnant and unexpectedly limited in extant robotic systems. This analysis indicates trends in increasing capacity in both internal and external complexity for natural systems while artificial, robotic systems have increased significantly in the capacity of computational (internal) states but remained more or less constant in mechanical (external) state capacity. This work presents a way to analyze trends in animal behavior and shows that robots are not capable of the same multi-faceted behavior in rich, dynamic environments as natural systems.
TRIF Regulates BIC/miR-155 via the ERK Signaling Pathway to Control the ox-LDL-Induced Macrophage Inflammatory Response

Toll/IL-1R-domain-containing adaptor-inducing IFN-β (TRIF) is an important adaptor for TLR3- and TLR4-mediated inflammatory signaling pathways. Recent studies have shown that TRIF plays a key role in vessel inflammation and atherosclerosis; however, the precise mechanisms are unclear. We investigated the mechanisms of the TRIF-regulated inflammatory response in RAW264.7 macrophages under oxidized low-density lipoprotein (ox-LDL) stimulation. Our data show that ox-LDL induces TRIF, miR-155, and BIC expression, activates the ERK1/2 and SOCS1-STAT3-NF-κB signaling pathways, and elevates the levels of IL-6 and TNF-α in RAW264.7 cells. Knockdown of TRIF using TRIF siRNA suppressed BIC, miR-155, IL-6, and TNF-α expression and inhibited the ERK1/2 and SOCS1-STAT3-NF-κB signaling pathways. Inhibition of ERK1/2 signaling also suppressed BIC and miR-155 expression. These findings suggest that TRIF plays an important role in regulating the ox-LDL-induced macrophage inflammatory response and that TRIF modulates the expression of BIC/miR-155 and the downstream SOCS1-STAT3-NF-κB signaling pathway via ERK1/2. Therefore, TRIF might be a novel therapeutic target for atherosclerosis.
MIXGAN: Learning Concepts from Different Domains for Mixture Generation

In this work, we present an interesting attempt on mixture generation: absorbing different image concepts (e.g., content and style) from different domains and thus generating a new domain with learned concepts. In particular, we propose a mixture generative adversarial network (MIXGAN). MIXGAN learns concepts of content and style from two domains respectively, and thus can join them for mixture generation in a new domain, i.e., generating images with content from one domain and style from another. MIXGAN overcomes the limitation of current GAN-based models which either generate new images in the same domain as they observed in training stage, or require off-the-shelf content templates for transferring or translation. Extensive experimental results demonstrate the effectiveness of MIXGAN as compared to related state-of-the-art GAN-based models.
Diet form and by-product level affect growth performance and carcass characteristics of grow-finish pigs

Two experiments were conducted to determine the effect of diet form and by-product (BP) level on growth performance and carcass characteristics of grow-finish pigs. In experiment 1, 384 pigs (22.2 ± 0.27 kg BW; 12 pigs/pen) were randomly assigned to one of the following treatments in a 2 × 2 arrangement: 1) low BP (LBP) meal [30% dried distiller grains with solubles (DDGS) and 15% wheat middlings (WM)] or 2) high BP (HBP) meal (50% DDGS and 15% WM) with diets fed either in meal or pellet form. In experiment 2, 1008 pigs (23.7 ± 0.27 kg BW; 21 pigs/pen) were randomly assigned to one of the following treatments in a 2 × 3 arrangement: 1) corn-soybean meal (CSBM), 2) LBP meal (25% DDGS and 7.5% WM), or 3) HBP meal (50% DDGS and 15% WM) with diets fed either in meal or pellet form. In both experiments, complete blocks of pigs were marketed when each block reached approximately 130 kg BW. In experiment 1, ADG was greater (P < 0.01) for pigs fed pelleted vs. meal diets. Increasing by-products in meal diets reduced ADFI, but not in pelleted diets (P < 0.05; diet form × BP level). Increasing by-products in meal diets improved G:F, but this did not occur when pelleted diets were fed (P < 0.05; diet form × BP level). In experiment 2, G:F was improved (P < 0.01) when diets were fed as a pellet vs. meal. Increasing by-product level decreased (P < 0.01) G:F. As BP level increased in meal diets ADG decreased, while increasing BP level in pelleted diets decreased ADG to a lesser extent (P < 0.05; diet form × BP level). As BP level increased, ADFI tended to decrease when meal diets were fed but not when pelleted diets were fed (P < 0.10; diet form × BP level). Increasing BP level decreased (P < 0.05) carcass yield and backfat. Pelleting tended (P < 0.10) to increase carcass yield. These data suggest that pelleting high by-product diets improves performance, and pelleting lessens the negative effects of by-product level on pig performance.
Anterior communicating artery aneurysm clipping versus coiling: a comparative study of 50 cases

Abstract Introduction: Aneurysmal Subarachnoid Hemorrhage (aSAH) remains a devastating and often fatal form of stroke. The aneurysm is targeted for obliteration to prevent re-bleeding and to manage the possible complications from the event. Endovascular coiling has emerged as a less invasive alternative to conventional surgical clipping to treat aneurysms. Patients and methods: This study was done in 50 cases of anterior communicating (Acommm) aneurysm presented in the department of neurosurgery, SMS medical college, Jaipur from November 2015 to August 2016 to evaluate the outcome of both modalities used in the treatment of ruptured Acommm aneurysm. 50 patients with Hunt and Hess (H&H) grade I, II or III were classified into two groups of microsurgical clipping and endovascular coiling. Results: Mortality rate was comparable in both groups that were 21. 21% in the clipping group and 23. 52% in the coiling group. Good Glasgow outcome score (GOS) were found in 60. 60% of clipping and 58. 58% of coiling group. All the complications found to be more in clipping group but that were not statistically significant except for hyponatremia which was significantly higher in clipping group(P=0. 007). Conclusion: There was no statistically significant difference in GOS at 6 month of follow up between the two groups. We recommend further interventional studies with larger sample sizes and longer follow up for better evaluation of the modalities.
Edge-CoCaCo: Toward Joint Optimization of Computation, Caching, and Communication on Edge Cloud

With the development of recent innovative applications (e.g., augmented reality, natural language processing, and various cognitive applications), more and more computation-intensive and rich-media tasks are delay-sensitive. Edge cloud computing is expected to be an effective solution to meet the demand for low latency. By the use of content offloading and/or computation offloading, users' quality of experience is improved with shorter delay. Compared to existing edge computing solutions, this article introduces a new concept of computing task caching and gives the optimal computing task caching policy. Furthermore, joint optimization of computation, caching, and communication on the edge cloud, dubbed Edge-CoCaCo, is proposed. Then we give the solution to that optimization problem. Finally, the simulation experimental results show that compared to the other schemes, Edge-CoCaCo has shorter delay.
Genesis of large siliceous stromatolites at Frying Pan Lake, Waimangu geothermal field, North Island, New Zealand

Lilypad stromatolites, up to 3 m long and 1·5 m wide, were found to be actively growing in the shallow marginal waters of Frying Pan Lake and its outflow channel. These stromatolites, composed of Phormidium (> 90%), Fischerella, and a variety of other microbes, develop through a series of distinct growth stages. Dark green microbial mats cover the floor of the outflow channel and give rise to columns of various sizes and shapes in the shallower marginal waters. Once the columns reach the water level, the mats spread laterally to form a lilypad stromatolite. The lilypads are characterized by a raised, dark green rim, 4–5 mm high, that encircles a flat interior covered with a distinctive orange‐red mat. The microbes forming the columns and lilypad plate are being actively silicified. The stromatolites are formed of: (i) flat‐lying Phormidium filaments (P‐laminae), (ii) upright filaments of Phormidium that are commonly associated with Fischerella (U‐laminae), and (iii) mucus, diatoms and pyrite framboids (M‐laminae). P‐laminae dominate most of the columns, with tripartite cycles of P‐, U‐, to M‐laminae being found mostly in the upper parts of the stromatolites. The transition from the P‐ to U‐laminae is marked by a change in the growth pattern of the Phormidium and branching of Fischerella, which was probably triggered by a change in environmental conditions. In the Frying Pan Lake outflow channel, this change may be related to fluctuations in water level and flow rates that are caused by periods of heavy rain, seasonal changes, long‐term variations in rainfall, and/or the unique 40‐day hydrological cycle that exists between Frying Pan Lake and Inferno Crater, which is a nearby hydrothermal crater lake.
Autologous Stem Cell Therapy in Critical Limb Ischemia: A Meta-Analysis of Randomized Controlled Trials

Objective Critical limb ischemia (CLI) is the most dangerous stage of peripheral artery disease (PAD). Many basic researches and clinical treatment had been focused on stem cell transplantation for CLI. This systematic review was performed to review evidence for safety and efficacy of autologous stem cell therapy in CLI. Methods A systematic literature search was performed in the SinoMed, PubMed, Embase, ClinicalTrials.gov, and Cochrane Controlled Trials Register databases from building database to January 2018. Results Meta-analysis showed that cell therapy significantly increased the probability of ulcer healing (RR = 1.73, 95% CI = 1.45–2.06), angiogenesis (RR = 5.91, 95% CI = 2.49–14.02), and reduced the amputation rates (RR = 0.59, 95% CI = 0.46–0.76). Ankle-brachial index (ABI) (MD = 0.13, 95% CI = 0.11–0.15), TcO2 (MD = 12.22, 95% CI = 5.03–19.41), and pain-free walking distance (MD = 144.84, 95% CI = 53.03–236.66) were significantly better in the cell therapy group than in the control group (P < 0.01). Conclusions The results of this meta-analysis indicate that autologous stem cell therapy is safe and effective in CLI. However, higher quality and larger RCTs are required for further investigation to support clinical application of stem cell transplantation.
Uncertainty Quantification of Electronic and Photonic ICs with Non-Gaussian Correlated Process Variations

Since the invention of generalized polynomial chaos in 2002, uncertainty quantification has impacted many engineering fields, including variation-aware design automation of integrated circuits and integrated photonics. Due to the fast convergence rate, the generalized polynomial chaos expansion has achieved orders-of-magnitude speedup than Monte Carlo in many applications. However, almost all existing generalized polynomial chaos methods have a strong assumption: the uncertain parameters are mutually independent or Gaussian correlated. This assumption rarely holds in many realistic applications, and it has been a long-standing challenge for both theorists and practitioners. This paper propose a rigorous and efficient solution to address the challenge of non-Gaussian correlation. We first extend generalized polynomial chaos, and propose a class of smooth basis functions to efficiently handle non-Gaussian correlations. Then, we consider high-dimensional parameters, and develop a scalable tensor method to compute the proposed basis functions. Finally, we develop a sparse solver with adaptive sample selections to solve high-dimensional uncertainty quantification problems. We validate our theory and algorithm by electronic and photonic ICs with 19 to 57 non-Gaussian correlated variation parameters. The results show that our approach outperforms Monte Carlo by 2500× to 3000× in terms of efficiency. Moreover, our method can accurately predict the output density functions with multiple peaks caused by non-Gaussian correlations, which is hard to handle by existing methods. Based on the results in this paper, many novel uncertainty quantification algorithms can be developed and can be further applied to a broad range of engineering domains.
MEASUREMENT AND MODELING OF THREE DIMENSIONAL TARGET STRENGTH OF FISH FOR HORIZONTAL SCANNING SONAR

This paper discusses the three-dimensional target strength (3DTS) of fish for a horizontal scanning sonar. Experiments were conducted in a tank using a defrosted Japanese mackerel. Measurements were made by changing the horizontal incident angle of a 50 kHz acoustic beam and the pitch angle of a tethered fish. Following the experiment, morphological characteristics, including the swimbladder size and shape, were measured using soft X-ray and digitized. The theoretical 3DTS was estimated using the prolate spheroid model and compared with the measured 3DTS. Results showed that the TS strongly depended on the fish orientation. The maximum and minimum TS were recorded at the broadside and the head/tail aspect of the fish, respectively. The horizontally averaged TS, which is necessary to estimate fish abundance by horizontal scanning sonar, gradually increased as the pitch angle increased, showing a minimum at 0° and maximum at 90°. The measured horizontally averaged TS was 3-5 dB lower than the theoretically estimated TS. Possible theoretical, biological, and technical reasons are discussed.
Harnessing Oxidative Stress as an Innovative Target for Cancer Therapy

Department of Oncology, University of Alberta, Edmonton, AB, Canada Department of Physiology, University of Lausanne, Lausanne, Switzerland Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada Research Institute in Oncology and Hematology, CancerCare Manitoba, Winnipeg, MB, Canada
A New Scheme to Estimate Median Progression-free Survival Time in Oncology Clinical Trials

Progression-free survival (PFS) has been accepted as a valid primary endpoint in many previous anti-tumor therapeutic product marketing approvals. Yet, it has been long known that current standard statistical methods to handle PFS data widely adopted in pharmaceutical industry may lead to serious bias under certain circumstances. Although most statistical issues related to two or multiple treatment group comparison problem for PFS data can be resolved (c.f. [10]), the challenge to provide a practical and better median PFS estimation still remains, which is an even more important question to address in order to get a thorough understanding of the treatment effect in everyday medical practice. In this paper, the author proposes a simple alternative trial design idea together with a new estimation scheme to solve this issue. The performance of the new method based on this new scheme will be compared to the standard method currently used by the pharmaceutical industry via simulations under typical oncology study settings.
Effect of Gibberellic and Salicylic Acids Pre-Soaking on Seed Germination Attributes of Cucumber (Cucumis sativus L.) under Induced Salt Stress

Saline stress is one of the most deleterious abiotic stress determining a considerable reduction in agricultural production. Seed germination is the primitive plant growth stage and considered as vulnerable to saline stress. However, the exogenous application of natural plant growth regulators has been reported as one of the mitigation strategies. A Petri dish experiment under controlled conditions was conducted at King Saud University. The aim was to quantify the negative impact of induced saline stress (NaCl) on seed germination attributes and role of gibberellic acid (GA3) and salicylic acid (SA) to reduce the inhibitory effect of saline stress on cucumber (Cucumis sativus L.) seeds. The treatments consist of two sets as: seed pre-soaking solution and NaCl stress. Five pre-soaking solutions were prepared as: H₂O (control), GA3 (100 ppm), GA3 (200 ppm), SA (0.5 ppm) and SA (1.0 ppm). While saline stress was imposed by NaCl at three levels such as: no stress (distilled water, control), mild stress (NaCl, 50 mM) and higher stress (NaCl, 100 mM). Results depicted that NaCl induced stress has significantly affected the all studied germinations attributes. The maximum NaCl stress (100 mM) stood highest in inhibiting seed germination percentage, seedling length, and seedling fresh and dry weights, followed by mild stress and control, respectively. Seed pre-soaking treatments were recorded non-significant for seedling length, fresh and dry weights while significant for germination percentage and number of seeds germinated over period of time. The interaction between seed pre-soaking treatments and induced saline stress was recorded significant. Overall, GA3 at the rate of 100 ppm solution performed a contributory role to mitigate the negative effect of saline stress.
Assessment of Operating Condition Dependent Reliability Indices in Microgrids

Reliability results are important for proper planning and operation of utility companies. At the base of this method of analysis is the failure rate of the system components. In the traditional method, this probability of failure is determined by the components’ manufacturer and is considered to be constant. This study proposes a dynamic modeling of failure rate, taking the system operating conditions into consideration. With this new consideration, an IEEE test system has seven of its reliability indices quantified for comparison. The inclusion of the newly modeled failure rate leads to a worsening of 11.07% in the indices, on average. A second analysis is performed considering the presence of DG sources within the microgrid, namely PV and wind based. An improvement of 0.71% on the indices is noticed, once the DG sources are introduced. Finally, the effects of storage systems in the microgrid are investigated through a third scenario, in which two 2 MWh battery systems are introduced, and an improvement of 3.05% is noticed in the reliability indices.
SGAD: Soft-Guided Adaptively-Dropped Neural Network

Deep neural networks (DNNs) have been proven to have many redundancies. Hence, many efforts have been made to compress DNNs. However, the existing model compression methods treat all the input samples equally while ignoring the fact that the difficulties of various input samples being correctly classified are different. To address this problem, DNNs with adaptive dropping mechanism are well explored in this work. To inform the DNNs how difficult the input samples can be classified, a guideline that contains the information of input samples is introduced to improve the performance. Based on the developed guideline and adaptive dropping mechanism, an innovative soft-guided adaptively-dropped (SGAD) neural network is proposed in this paper. Compared with the 32 layers residual neural networks, the presented SGAD can reduce the FLOPs by 77% with less than 1% drop in accuracy on CIFAR-10.