Miracle-dz/UniFAR-FTUs huggingface dataset:
Technical Feasibility of Transnasal Endoscopic Anterior Ethmoid Artery Ligation: Assessment with Intraoperative Ct Imaging

Background The objective of this study was to evaluate the technical feasibility of endoscopic anterior ethmoid artery (AEA) ligation for acute control of epistaxis. Methods A prospective study was conducted using eight cadaver heads. Pre- and intraoperative CT scans were performed using the xCAT (Xoran Technologies, Inc., Ann Arbor, MI). Skull base anatomy relative to the AEA was reviewed preoperatively. Endoscopic AEA ligation was attempted in all sides with a mesentery. Ligation was not deemed feasible in AEAs without a mesentery. It was attempted on two sides without a mesentery to assess risk of skull base and orbital disruption. Intraoperative CT scans were performed to assess the position of the clips and the integrity of the skull base and lamina papyracea. Results The mean lateral lamella height was 4.75 and 4.83 mm on the right and left, respectively. Of the 16 arteries, 6 (37.5%) of the AEAs were within a bony mesentery. No AEA canals were dehiscent. Four of the six AEAs (66%) within a mesentery were successfully clipped and two (33%) were partially clipped by endoscopic evaluation. Both arteries without mesentery where clipping was attempted were partially clipped by endoscopic examination. Review of intraoperative CT scans showed that the AEA with a mesentery was clipped successfully on three sides, partially on one side, and unsuccessfully on two sides. AEA clipping was unsuccessful on both sides without a mesentery. One AEA without a mesentery showed skull base disruption after ligation by endoscopy and CT. None of the specimens showed orbital injury. Conclusion Intraoperative CT scanning revealed that AEA ligation was less successful than was apparent endoscopically. Effective AEA clipping was performed in 50% of cases with a mesentery. Endoscopic clipping was not technically feasible in cases with AEA without a mesentery. Overall, AEA clipping was only technically feasible in 3 of 16 sides (18.8%).
Victim Issues Are Key to Effective Sex Offender Treatment

The recent passage of Sexually Violent Predator laws in several states has increased interest in identifying those sex offenders most likely to re-offend and changeable or dynamic factors that can be most effectively addressed in treatment in order to reduce sex offender recidivism. Hanson and his colleagues have identified the following as promising stable dynamic factors: intimacy deficits, negative peer influences, attitudes tolerant of sexual offending, problems with emotional/sexual self-regulation, and general self-regulation. On the basis of 25 years experience treating sex offenders, as well as the growing literature on the effects of early trauma on the development of the brain, the author explores the relationships among these factors and the long-term effects of child abuse.
Optimization Deployed Strategy of Wireless Power Beacon based on 5G Millimeter Wave Cooperative Communication Small Cell

To realize the green communication with high spectrum efficiency and low energy consumption in 5G wireless network, a small cell network model of millimeter was cooperative communication of user equipment devices with high-low frequency hybrid networking was constructed for 5G edge network. On the basis of this model, in order to improve the spectrum efficiency and energy harvesting coverage of edge system, an optimized deployment strategy of small cell wireless power beacon based on 5G mm wave cooperative communication was proposed. By minimizing the number of power beacons(PBs) in fixed charging, the normal operation of the system was guaranteed on the basis of minimizing the system energy consumption. As the optimization problem is a NP hard problem, a greedy algorithm with constant factors was designed to approximate the optimization problem. Theoretical analysis proves the feasibility of the algorithm. Simulation results show that this strategy can effectively optimize the PBs deployment, and the energy consumption is the lowest under the same coverage and regional spectral efficiency gain.
Compensation: Role and Ramifications in Biomolecular Ligand Recognition and Design

Recent calorimetric studies of interactions between small molecules and biomolecular targets have generated renewed interest in the phenomenon of entropy-enthalpy compensation. In these studies, entropic and enthalpic contributions to binding are observed to vary substantially and in an opposing manner as the ligand or protein is modified, whereas the binding free energy varies little. In severe examples, engineered enthalpic gains can lead to completely compensating entropic penalties, frustrating ligand design. Here, we examine the evidence for compensation, as well as its potential origins, prevalence, severity, and ramifications for ligand engineering. We find the evidence for severe compensation to be weak in light of the large magnitude of and correlation between errors in experimental measurements of entropic and enthalpic contributions to binding, though a limited form of compensation may be common. Given the difficulty of predicting or measuring entropic and enthalpic changes to useful precision, or using this information in design, we recommend ligand engineering efforts instead focus on computational and experimental methodologies to directly assess changes in binding free energy.
Real-time prediction learning for the simultaneous actuation of multiple prosthetic joints

Integrating learned predictions into a prosthetic control system promises to enhance multi-joint prosthesis use by amputees. In this article, we present a preliminary study of different cases where it may be beneficial to use a set of temporally extended predictions - learned and maintained in real time - within an engineered or learned prosthesis controller. Our study demonstrates the first successful combination of actor-critic reinforcement learning with real-time prediction learning. We evaluate this new approach to control learning during the myoelectric operation of a robot limb. Our results suggest that the integration of real-time prediction and control learning may speed control policy acquisition, allow unsupervised adaptation in myoelectric controllers, and facilitate synergies in highly actuated limbs. These experiments also show that temporally extended prediction learning enables anticipatory actuation, opening the way for coordinated motion in assistive robotic devices. Our work therefore provides initial evidence that realtime prediction learning is a practical way to support intuitive joint control in increasingly complex prosthetic systems.
Managing high penetration of renewable energy in MV grid by electric vehicle storage

This paper proposes an intelligent algorithm for dealing with high penetration of renewable energy sources (RESs) in the medium voltage (MV) by intelligently managing electric vehicles (EVs), as one of the grid flexible loads. The MV grid used in this work is a CIGRE benchmark grid. Different residential and industrial loads are considered in this grid. The connection of medium voltage wind turbines to the grid is investigated. The solar panels in this study are residential panels. Also, EVs are located among the buses with residential demand. The study is done for different winter and summer scenarios, considering typical load profiles in Denmark. Different scenarios have been studied with different penetration level of RESs in the grid. The results show the capability of the proposed algorithm to reduce voltage deviations among the grid buses, as well as to increase the RES penetration in the grid by intelligent management of EVs.
Trajectory Planning Algorithm of Manipulator in Small Space Based on Reinforcement Learning

The development of reinforcement learning has driven the progress of robot control technology. In recent years, reinforcement learning has become one of the highly concerned fields in the academic community, especially the control of robotic arms in the industrial field. In order to achieve intelligent and efficient production, the emphasis is on the research of obstacle avoidance motion planning of the manipulator. However, traditional trajectory planning algorithms have problems such as slow convergence speed, low intelligence, and difficulty in achieving optimization. In this regard, this research takes the six degrees of freedom manipulator PUMA550 as the research object, and focuses on the obstacle avoidance motion planning problem of the manipulator, studies the manipulator modeling based on the improved D-H parameter method, Rapidly-exploring Random Trees (RRT) algorithm, the Q-learning algorithm and the double Q network learning alzorithm.
Mixed-Signal Dot-Product Processor with Switched-Capacitors for Machine Learning

A mixed-signal dot-product computation has growing use cases in embedded sensory systems and emerging computing platforms (such as in-memory or neuromorphic computings) for the ultra low-power implementation of machine learning (ML) algorithms. This paper proposes a compact and energy-efficient mixed-signal dot-product circuit with switched-capacitors which has an analog input as one operand and a digital input as the other operand. The proposed dot-product processor requires only two unit-sized capacitors per multiplication, thereby highly energy- and area-efficient. The proposed processor also supports flexible input bit-precision without any hardware overhead by simply iterating more cycles to provide higher bit precision. The simulated results for the proposed circuit designed in a 14nm CMOS show 10.5× and 7.9× improvements in energy efficiency and computation delay, respectively, compared to a conventional switched-capacitor based implementation while maintaining 9 bit output resolution.
Prediction of the Interactive Dynamics of Stimulated Emotions: Chaos, Limit Cycles and Stability

The paper attempts to model the interactive dynamics of competitive/co-operative emotions, aroused by audio-visual stimulus. Parameter variations of the dynamics results in three specific dynamic behavior including chaos, limit cycles and stability. An analysis of the dynamics yields the parametric conditions for stability and chaos. Known audio-visual stimulus is used to predict the emotive state of the dynamics from the external manifestation of emotions in the facial expressions of the subjects. Such prediction helps in early detection of trauma and epilepsy.
Online synthesis for operation execution time variability on digital microfluidic biochips

Several approaches have been proposed for the synthesis of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determine the allocation, resource binding, scheduling, placement and routing of the operations in the application. Researchers have assumed that each biochemical operation in an application is characterized by a worst-case execution time (wcet). However, during the execution of the application, due to variability and randomness in biochemical reactions, operations may finish earlier than their wcets. In this paper we propose an online synthesis strategy that re-synthesizes the application at runtime when operations experience variability in their execution time, obtaining thus shorter application execution times. The proposed strategy has been evaluated using several benchmarks.
Optimal Policy for Software Vulnerability Disclosure

Software vulnerabilities represent a serious threat to cybersecurity, most cyberattacks exploit known vulnerabilities. Unfortunately, there is no agreed-upon policy for their disclosure. Disclosure policy (which sets a protected period given to a vendor to release the patch for the vulnerability) indirectly affects the speed and quality of the patch that a vendor develops. Thus, CERT/CC and similar bodies acting in the public interest can use disclosure to influence the behavior of vendors and reduce social cost. This paper develops a framework to analyze the optimal timing of disclosure. We formulate a model involving a social planner who sets the disclosure policy and a vendor who decides on the patch release. We show that the vendor typically releases the patch less expeditiously than is socially optimal. The social planner optimally shrinks the protected period to push the vendor to deliver the patch more quickly, and sometimes the patch release time coincides with disclosure. We extend the model to allow the proportion of users implementing patches to depend upon the quality (chosen by the vendor) of the patch. We show that a longer protected period does not always result in a better patch quality. Another extension allows for some fraction of users to use “work-arounds. ” We show that the possibility of work-arounds can provide the social planner with more leverage, and hence the social planner shrinks the protected period. Interestingly, the possibility of work-arounds can sometimes increase the social cost due to the negative externalities imposed by the users who are able to use the work-arounds on the users who are not.
Abstractions in Judgment: Does Construal Level Influence the System Specific Reasoning of Dual Process Theory?

ions in Judgment: Does Construal Level Influence the System Specific Reasoning of Dual Process Theory? Karl Drejing karl.drejing@gmail.com Recent research have proposed a link between two large theoretical bodies, namely the Construal Level Theory (CLT) and the Dual Process Theory (DPT). The proposed connection is that DPT systems share characteristics with CLT constructs; that systems operate at different levels of abstraction. While these claims have been made, there has been no direct attempt to scrutinize the implication. The hypothesis that a link between these theories exists is examined empirically in this paper. We investigate whether people respond in a DPT system specific way when primed with different levels of construal. 89 high school students were primed with different levels of construal and performed binary choice judgments of either easy or hard difficulty. We expected that the percent of correct judgments that participants made while primed with a lowlevel construal would be higher than participants primed with a high-level construal, in the easy condition. Conversely, we expected that the percent of correct judgments that participants made while primed with a high-level construal would be higher than participants primed with a low-level construal, in the hard condition. The results indicate that there is no such connection. We discuss whether this result is due to diminishing priming and/or a failure to replicate other studies.
Application Research of Wide&Deep Model in CATV Intelligent Video Recommendation System

Wasu Media & Network Co., Ltd has recently launched a brand-new intelligent cable television terminal with much improved hardware performance and optimized compute capacity. This infrastructure upgrade calls for a better recommendation system to serve users with higher accuracy, greater computing efficiency and more timely recommendations. This paper mainly introduces the practice and application of the recommendation model based on Wide&Deep in CATV Intelligent video recommendation. Provide algorithm solutions for the construction of real-time CATV intelligent recommendation systems.
Beneficial effects of switching from beta-blockers to nebivolol on the erectile function of hypertensive patients.

AIM To investigate the effect of substituting beta-blockers with nebivolol on the erectile function of patients suffering from essential hypertension. METHODS Forty-four young and middle-aged men (31-65 years) with essential hypertension visited our outpatient clinic and took beta-blocker treatment (atenolol, metoprolol or bisoprolol) for more than 6 months. All the patients completed a questionnaire regarding erectile function (International Index for Erectile Function). Patients were then switched to an equipotent dose of nebivolol for 3 months and, at the end of this time period, filled out the same questionnaire. RESULTS Twenty-nine out of the 44 (65.9%) patients who took beta-blockers (atenolol, metoprolol or bisoprolol) had exhibited erectile dysfunction (ED). Their systolic and diastolic blood pressure did not change significantly with the treatment switch. In 20 out of these 29 (69%) patients, a significant improvement in the erectile function score was exhibited after 3 months of nebivolol administration, and in 11 of these 20 patients, erectile function was normalized. CONCLUSION Nebivolol seems to have a beneficial effect on ED (possibly due to increased nitric oxide availability); however, further prospective, randomized, placebo-controlled studies are needed to confirm the beneficial effects of nebivolol.
Pattern Matching and Discourse Processing in Information Extraction from Japanese Text

Information extraction is the task of automatically picking up information of interest from an unconstrained text. Information of interest is usually extracted in two steps. First, sentence level processing locates relevant pieces of information scattered throughout the text; second, discourse processing merges coreferential information to generate the output. In the first step, pieces of information are locally identified without recognizing any relationships among them. A key word search or simple pattern search can achieve this purpose. The second step requires deeper knowledge in order to understand relationships among separately identified pieces of information. Previous information extraction systems focused on the first step, partly because they were not required to link up each piece of information with other pieces. To link the extracted pieces of information and map them onto a structured output format, complex discourse processing is essential. This paper reports on a Japanese information extraction system that merges information using a pattern matcher and discourse processor. Evaluation results show a high level of system performance which approaches human performance.
BiLSTM-TCN: An Aerial Target Intent Recognition Model

This study presents a novel deep learning method called BiLSTM-TCN, which aims to enhance the proficiency of recognizing air target operational intent. The traditional air target operational intent method makes judgments based on single moment data, and thus cannot effectively capture feature information on temporal data. To tackle this issue, we select suitable features for air target intent feature set construction and then encode them into time-series features. We mine the potential feature information in the data by TCN. Meanwhile, we captured the prolonged correlations within the dataset by using BiLSTM. Through experimental validation, we have shown that BiLSTM-TCN surpasses current superior techniques regarding the accuracy of identifying airborne targets' intentions.
SVM-MLP-PNN Classifiers on Speech Emotion Recognition Field - A Comparative Study

In this paper, we present a comparative analysisof three classifiers for speech signal emotion recognition.Recognition was performed on emotional Berlin Database.This work focuses on speaker and utterance (phrase)dependent and independent framework. One hundred thirtythree (133) sound/speech features were extracted from Pitch,Mel Frequency Cepstral Coefficients, Energy and Formantsand were evaluated in order to create a feature set sufficient todiscriminate between seven emotions in acted speech. A set of26 features was selected by statistical method and MultilayerPercepton, Probabilistic Neural Networks and Support VectorMachine were used for the Emotion Classification at sevenclasses: anger, happiness, anxiety/fear, sadness, boredom,disgust and neutral. In speaker dependent framework,Probabilistic Neural Network classifier reached very highaccuracy of 94%, whereas in speaker independent framework,Support Vector Machine classification reached the bestaccuracy of 80%. The results of numerical experiments aregiven and discussed in the paper.
ROCR: visualizing classifier performance in R

UNLABELLED ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It features over 25 performance measures that can be freely combined to create two-dimensional performance curves. Standard methods for investigating trade-offs between specific performance measures are available within a uniform framework, including receiver operating characteristic (ROC) graphs, precision/recall plots, lift charts and cost curves. ROCR integrates tightly with R's powerful graphics capabilities, thus allowing for highly adjustable plots. Being equipped with only three commands and reasonable default values for optional parameters, ROCR combines flexibility with ease of usage. AVAILABILITY http://rocr.bioinf. mpi-sb.mpg. de. ROCR can be used under the terms of the GNU General Public License. Running within R, it is platform-independent. CONTACT tobias.sing@mpi-sb.mpg. de.
BASS: BitTorrent Assisted Streaming System for Video-on-Demand

This paper introduces a hybrid server/P2P streaming system called bittorrent-assisted streaming system (BASS) for large-scale video-on-demand (VoD) services. By distributing the load among P2P connections as well as maintaining active server connections, BASS can increase the system scalability while decreasing media playout wait times. To analyze the benefits of BASS, we examine torrent trace data collected in the first week of distribution for Fedora Core 3 and develop an empirical model of bittorrent client performance. Based on this, we run trace-based simulations to evaluate BASS and show that it is more scalable than current unicast solutions and can greatly decrease the average waiting time before playback
Material Matters: Gender and the City

This article provides a review of contemporary literature related to gender and the city, drawing primarily from Anglo-American feminist geography, but also architecture and urban planning. It first reflects back on early feminist interventions in the modern city, often referred to as the ‘municipal housekeeping’ movement or early ‘feminist materialism’. In this movement, middle-class female reformers drew upon ideological associations between women and homes to address ‘material’ concerns related to home/housing, health, and urban politics. I reflect on this activism to raise awareness of early feminist praxis and to suggest that these three themes (and the materiality that links them) remain important areas for investigation within feminist geography, especially as cities have been ravaged by neoliberal austerity and are embroiled in a global recession. Using new feminist materialism as an organizing theme, I argue for a refined and reinvigorated material gendered urban research that addresses home/housing, health, and urban politics. This feminist materialism is decoupled from restrictive versions of structuralism, attentive to embodiment, encompassing of intersectionalities, focused on the everyday and beyond, and attuned to social justice and feminist praxis.