Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-related requisite concentration of sevoflurane for adequate sedation with combined epidural-general anesthesia

Background The requisite anesthetic concentration of sevoflurane required to obtain adequate sedation when sufficient analgesics are supplied has not been determined. The purpose of this study was to determine the requisite age-associated concentration of sevoflurane to obtain an adequate level of anesthesia during combined epidural-general anesthesia by bispectral index (BIS) monitoring. Methods Twenty-seven elective abdominal surgery patients (American Society of Anesthesiologists physical status I-II) were enrolled. The patients were divided into two groups of more or less than 60 years of age. We investigated the concentration of sevoflurane required to obtain an adequate sedation level during combined epidural-general anesthesia, maintaining the BIS value between 40 and 60. Results The requisite sevoflurane concentration required to keep the BIS value at 40-60 was not stable during surgery. In the younger group, the maximum concentration of sevoflurane needed during surgery was 1.95 ± 0.14 (95% confidence interval: 1.87-2.10) vol%, while it was 1.54 ± 0.44 (95% confidence interval: 1.27-1.80) vol% in the older group (P < 0.01). Conclusions The requisite concentration of sevoflurane required with combined epidural-general anesthesia was 2.5 vol% for the younger group and 2.0 vol% for the older group as determined by BIS monitoring. We believe that these percentages are sufficient to avoid awareness during surgery with adequate analgesia.
MSRA-USTC-SJTU at TRECVID 2007: High-Level Feature Extraction and Search

This paper describes the MSRA-USTC-SJTU experiments for TRECVID 2007. We performed the experiments in high-level feature extraction and automatic search tasks. For high-level feature extraction, we investigated the benefit of unlabeled data by semi-supervised learning, and the multi-layer (ML) multi-instance (MI) relation embedded in video by MLMI kernel, as well as the correlations between concepts by correlative multi-label learning. For automatic search, we fuse text, visual example, and concept-based models while using temporal consistency and face information for re-ranking and result refinement.
Compressive properties and column efficiency of metals reinforced on the surface with bonded filaments

Abstract : A design concept which could be utilized during the development period of the all composite structure is that of enhancing conventionally designed metallic structures with resin bonded filaments. This concept has considerable practical merit, since it retains the large background of technology developed for metal aircraft. For example, considerable weight saving is indicated if the longitudinal elements of monocoque structures are surface reinforced with axially alined filaments. The axially loaded filaments are utilized efficiently and minimum amounts of the filamentary material are required. Shear stresses and inplane direct stresses are supported by the metal structure. The purpose of this paper is to report the results of an exploratory research program conducted to determine the potential for weight saving offered by conventional metals reinforced on the surface with resin bonded filaments. The program involved a series of filament reinforced tubular compression specimens designed to indicate feasibility and to provide the strength and stiffness values necessary to demonstrate the weight saving potential of filament reinforced metals. The compressively loaded tube was selected for study because it lends itself conveniently to filamentary reinforcement and laboratory testing. In addition, tube columns are attractive because of the relatively simple and well developed analytical expressions for load carrying capacity and structural efficiency.
Facial Expression Recognition: A Survey

- Face Expression plays an important role in human communication. Facial Expression Recognition (FER) is process performed by computers which consist of detect the face in the image and preprocess the face region, extracting facial expression features from image by analyzing the motion of facial features or change in the appearance of facial features and classifying this information into facial expression categories like prototypic facial expression such as fear, happy, sad or Action Units(AU) such as eye open or mouth stretched. Face Expression Recognition techniques have always been a very challenging task in real life applications because of the variations in the illumination, pose and occlusion. This paper presents a methodology for face expression recognition.
Genetic Modulation of Lipid Profiles following Lifestyle Modification or Metformin Treatment: The Diabetes Prevention Program

Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, P interaction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; P interaction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, P interaction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; P interaction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.
Design Quality of Security Service Negotiation Protocol

With future network equipment the security service becomes a criti- cal and serious problem. Especially in the network, users do not want to expose their message to others or to be forged by others. They make extensive use of cryptography and integrity algorithms to achieve security. The sender can achieve the high quality of security service (high security level), only if the receivers and routers along path to receivers can support or satisfy the quality of security service requested by the sender. Therefore, this paper proposes a protocol to provide the needed mechanism for quality of security service, to dynamically negotiate the qua- lity of security service among the senders and receivers of multicasts in the network. It provides different quality of security service resolutions to different receiver nodes with different security service needs and includes six different negotiation styles.
Identification of New Candidate Genes and Chemicals Related to Esophageal Cancer Using a Hybrid Interaction Network of Chemicals and Proteins

Cancer is a serious disease responsible for many deaths every year in both developed and developing countries. One reason is that the mechanisms underlying most types of cancer are still mysterious, creating a great block for the design of effective treatments. In this study, we attempted to clarify the mechanism underlying esophageal cancer by searching for novel genes and chemicals. To this end, we constructed a hybrid network containing both proteins and chemicals, and generalized an existing computational method previously used to identify disease genes to identify new candidate genes and chemicals simultaneously. Based on jackknife test, our generalized method outperforms or at least performs at the same level as those obtained by a widely used method - the Random Walk with Restart (RWR). The analysis results of the final obtained genes and chemicals demonstrated that they highly shared gene ontology (GO) terms and KEGG pathways with direct and indirect associations with esophageal cancer. In addition, we also discussed the likelihood of selected candidate genes and chemicals being novel genes and chemicals related to esophageal cancer.
A Multiharvested Self-Powered System in a Low-Voltage Low-Power Technology

A multiharvesting system conception focused on low-voltage (up to 2.5 V) and low-power applications is presented and validated as a point-of-view system. Using just this application-specified integrated circuit, with a total quiescent power consumption of 160 μW, the harvesting system is able to collect and manage energy from different power sources, such as solar light (indoor environment), vibration (low-voltage piezoelectric generators), and electromagnetic induction (operating with a carrier frequency of 13.56-MHz regulated band). The maximum total power harvested with the addition of the three harvesting sources is around 6.4 mW, for the operating conditions defined by a PZT at 7 m/s2 at 80 Hz, 1500 lx for a laboratory illumination, and 200 mW emitted by a base transmitter at 25-mm distance between coils. A broad and detailed description of all low-power-consumption circuits involved in the multiharvesting system is described, emphasizing their design for low-voltage and low-power applications.
AFM Fast Tip Approach Based on Fiber Optic Sensor

As AFM tip approach speed is one of the key factors for AFM industrial on-line detection application, a sectional fast tip approach method composed of rough approach and mild approach processes is introduced here. In rough approach process, AFM tip can be approached by step motor to certain distance upon the sample surface with high speed, as a homemade dual-channel reflective intensity modulated fiber optic displacement sensor (DC-RIMFODS) can be integrated to AFM scan head easily to detect the stop position. While continued with mild approach process after rough approach, step motor can run slowly with a common PI feedback controller for Z scanner to make the tip get in touch with sample surface softly. Experimental results show that with the well-defined fiber optical sensor positioning accuracy and repeatability, the tip-sample distance can be limited in certain range after rough approach with 1mm/s high speed, and the whole AFM tip approach process can be finished in 20s by continuing with mild approach, while the initial tip-sample distance is about 10mm.
Inferring private information using social network data

On-line social networks, such as Facebook, are increasingly utilized by many users. These networks allow people to publish details about themselves and connect to their friends. Some of the information revealed inside these networks is private and it is possible that corporations could use learning algorithms on the released data to predict undisclosed private information. In this paper, we explore how to launch inference attacks using released social networking data to predict undisclosed private information about individuals. We then explore the effectiveness of possible sanitization techniques that can be used to combat such inference attacks under different scenarios.
Tracking Mobile Phones on Interactive Tabletops

The number of ”interactive surface” systems, especially tabletop interfaces, in public is increasing. As more and more casual users interact with such systems, they may wish to use existing computing infrastructure, such as their mobile phone, in conjunction with the new interface. In this paper, we present a method to reliably detect and track unmodified mobile phones that are placed upon an interactive tabletop. Range detection and data exchange is done via Bluetooth, while the location of the phone is tracked through its shadow on the surface.
Automated gait discrimination using Hidden Markov Model

An automated gait pattern discrimination method based on Hidden Markov Model (HMM) was proposed in this paper. According to human gait process, the acceleration signals of human lower limb were divided into different segments and the gait features was extracted by wavelet transform. Then, each state of gait was matched with HMM state and the HMM of each gait mode was trained according to the sample. When the parameters of model are stable, we use the trained HMM to recognize acceleration feature and get the gait pattern ultimately. The experimental results show that HMM has a unique advantage in classification and recognition of timing varying signal.
Psychometric Analysis of the JSPE Nursing Student Version R: Comparison of Senior BSN Students and Medical Students Attitudes toward Empathy in Patient Care

Background. Empathic communication skills are critical to providing high-quality nursing care to holistically understand the patient's perspective. A survey research design was used to address the research questions discussed in this study. Data consisted of responses from nursing students attending accredited programs in the southeastern United Sates using the Jefferson Scale of Physician Empathy Nursing Student Version R (JSPE-R). Findings. Comparisons of the total scores from JSPE Versions S and R yielded similar means and standard deviations with 115 and 114.57, respectively, and standard deviations of 10 and 10.94, respectively. The results of a one-sample t-test failed to render statistical significance (t = −1.22, P = .224), indicating that the overall attitudes of nursing students and medical students are similar. The 25th, 50th, and 75th percentiles and overall instrument reliability were also comparable. Conclusions. This paper supports the emergence of alternative factor analysis structures as applied to nursing students through statistical progression from exploratory factor analysis to confirmatory structures. Implications for practice explore the utility of empathy instruments in nurse education, such as empathy progression through curriculum. As nursing educators, the utility of development of instruments to measure effectiveness of teaching strategies and pedagogy for empathy enhancement in practice is important.
Network Analysis Reveals Increased Integration during Emotional and Motivational Processing

In recent years, a large number of human studies have investigated large-scale network properties of the brain, typically during the resting state. A critical gap in the knowledge base concerns the understanding of network properties of a focused set of brain regions during task conditions engaging these regions. Although emotion and motivation recruit many brain regions, it is currently unknown how they affect network-level properties of inter-region interactions. In the present study, we sought to characterize network structure during “mini-states” engendered by emotional and motivational cues investigated in separate studies. To do so, we used graph-theoretic network analysis to probe network-, community-, and node-level properties of the trial-by-trial functional connectivity between regions of interest. We used methods that operate on weighted graphs that make use of the continuous information of connectivity strength. In both the emotion and motivation datasets, global efficiency increased and decomposability decreased. Thus, processing became less segregated with the context signaled by the cue (potential shock or potential reward). Our findings also revealed several important features of inter-community communication, including notable contributions of the bed nucleus of the stria terminalis, anterior insula, and thalamus during threat and of the caudate and nucleus accumbens during reward. Together, the results suggest that one way in which emotional and motivational processing affect brain responses is by enhancing signal communication between regions, especially between cortical and subcortical ones.
Machinability Evaluation in the Ultrasonic Drilling (USD) Process of Aluminum Oxide-based Ceramics

The ultrasonic drilling (USD) has been used in the manufacture of the hard, fragile, difficult to cut, nonconductive ceramic materials. In this study, the mathematical models of material removal rate (MRR) and surface roughness (SR) have been obtained for the machinability evaluation in the USD process of aluminum oxide-based ceramic material. The experimental plan adopts the face centered central composite design (CCD). The mathematical models using the response surface methodology (RSM) are developed so as to investigate the influences of three machining parameters, including the power rating, grit size and slurry concentration on the performance characteristics of MRR and SR. It has been proved that the proposed mathematical models in this study would fit and predict values of the performance characteristics, which would be close to the readings recorded in experiment with a 95% confidence level. The significant parameters that critically affect the performance characteristics are examined.
Metabolism of Prazosin in Rat, Dog, and Human Liver Microsomes and Cryopreserved Rat and Human Hepatocytes and Characterization of Metabolites by Liquid Chromatography/Tandem Mass Spectrometry

Prazosin (2-[4-(2-furanoyl)-piperazin-1-yl]-4-amino-6,7-dimethoxyquinazoline) is an antihypertensive agent that was introduced to the market in 1976. It has since established an excellent safety record. However, in vitro metabolism of prazosin has not been investigated. This study describes the in vitro biotransformation of prazosin in liver microsomes from rats, dogs, and humans, as well as rat and human cryopreserved hepatocytes and characterization of metabolites using liquid chromatography/tandem mass spectrometry. The major in vivo biotransformation pathways reported previously in rats and dogs include demethylation, amide hydrolysis, and O-glucuronidation. These metabolic pathways were also confirmed in our study. In addition, several new metabolites were characterized, including a stable carbinolamine, an iminium species, and an enamine—all formed via oxidation of the piperazine ring. Two ring-opened metabolites generated following oxidative cleavage of the furan ring were also identified. Using semicarbazide hydrochloride as a trapping agent, an intermediate arising from opening of the furan ring was captured as a pyridazine product. In the presence of glutathione, three glutathione conjugates were detected in microsomal incubations, although they were not detected in cryopreserved hepatocytes. These data support ring opening of the furan via a reactive γ-keto-α,β-unsaturated aldehyde intermediate. In the presence of UDP-glucuronic acid, prazosin underwent conjugation to form an N-glucuronide not reported previously. Our in vitro investigations have revealed additional metabolic transformations of prazosin and have shown the potential of prazosin to undergo bioactivation through metabolism of the furan ring to a reactive intermediate.
Grouping Photos by Face

Image organizers such as imgSeek and GIFT allow query by image content (QBIC). QBIC help users find duplicate and similar photos. However, the similarity is measured based on color, texture and shape, not in terms of people. We implemented a “query by face” feature for organizing personal digital photos, using face detection and recognition techniques. We used the OpenCV library to extract faces and combined Principal Components Analysis (PCA) and Locality Preserving Projections (LPP) for face matching. We observed acceptable accuracy in our experiment.
Mechanical Properties of Phenolic Resin Diafoams: Part 2

the factors which control the strength and modulus of organic foams and develop methods of reinforcing such foams. In the first publication, the preparation and evaluation of phenolic resin syntactic foams was investigated (1). The phenolic resin system was selected because of its good heat resistance and low flamma’bility combined with low cost which makes it attractive for building applications. Similar results were obtained with other thermosetting resins, as for example, epoxy and polyester resins. The addition of hollow inorganic microspheres (glass microballoons, fly ash, Silas balloons) alters the performance of organic foams in a predictable manner. The following experimental methods were used to establish the stress-strain be-
Large Volatility Matrix Inference via Combining Low-Frequency and High-Frequency Approaches

It is increasingly important in financial economics to estimate volatilities of asset returns. However, most of the available methods are not directly applicable when the number of assets involved is large, due to the lack of accuracy in estimating high-dimensional matrices. Therefore it is pertinent to reduce the effective size of volatility matrices in order to produce adequate estimates and forecasts. Furthermore, since high-frequency financial data for different assets are typically not recorded at the same time points, conventional dimension-reduction techniques are not directly applicable. To overcome those difficulties we explore a novel approach that combines high-frequency volatility matrix estimation together with low-frequency dynamic models. The proposed methodology consists of three steps: (i) estimate daily realized covolatility matrices directly based on high-frequency data, (ii) fit a matrix factor model to the estimated daily covolatility matrices, and (iii) fit a vector autoregressive model to the estimated volatility factors. We establish the asymptotic theory for the proposed methodology in the framework that allows sample size, number of assets, and number of days go to infinity together. Our theory shows that the relevant eigenvalues and eigenvectors can be consistently estimated. We illustrate the methodology with the high-frequency price data on several hundreds of stocks traded in Shenzhen and Shanghai Stock Exchanges over a period of 177 days in 2003. Our approach pools together the strengths of modeling and estimation at both intra-daily (high-frequency) and inter-daily (low-frequency) levels.
An inductor-less MPPT design for light energy harvesting systems

An inductor-less maximum power point tracker was designed for light energy harvesting systems. We target at systems under different lighting environments and sometimes the solar cell voltage may be low. A charge pump is used to convert the voltage to a higher value. At the same time, the control circuit tunes the charge pump switching frequency to track the system maximum output power point. The design was fabricated and measured to verify the system operation.
Quasilocal energy in loop quantum gravity

Although there is no known meaningful notion of the energy density of the gravitational field in general relativity, a few notions of quasilocal energy of gravity associated to extended but finite domains have been proposed. In this paper, the notions of quasilocal energy are studied in the framework of loop quantum gravity, in order to see whether these notions can be carried out at quantum level. Two basic quasilocal geometric quantities are quantized, which lead to well-defined operators in the kinematical Hilbert space of loop quantum gravity. We then use them as basic building blocks to construct different versions of quasilocal energy operators. The operators corresponding to Brown-York energy, Liu-Yau energy, Hawking energy, and Geroch energy are obtained, respectively. The virtue of the Geroch energy operator is that it is beneficial for us to derive a rather general entropy-area relation and thus a holographic principle from loop quantum gravity.