Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimally invasive image-guided therapies for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fifth most frequently occurring cancer globally and predominantly develops in the setting of various grades of underlying chronic liver disease, which affects management decisions. Image-guided percutaneous ablative or transarterial therapies have acquired wide acceptance in HCC management as a single treatment modality or combined with other treatment options in patients who are not amenable for surgery. Recently, such treatment modalities have also been used for bridging or downsizing before definitive treatment (ie, surgical resection or liver transplantation). This review focuses on the use of minimally invasive image-guided locoregional therapies for HCC. Additionally, it highlights recent advancements in imaging and catheter technology, embolic materials, chemotherapeutic agents, and delivery techniques; all lead to improved patient outcomes, thereby increasing the interest in these invasive techniques.
A methodology to evaluate the trustworthiness of Cloud service providers' availability

Cloud service providers (CSPs) compete among each other to guarantee very high availability of their services. The most common CSPs guarantee the availability of at least 99.9% (some even 100%) in their service level agreements (SLAs), i.e., they guarantee maximum 8.77 hours of downtime per year for their services. However, this high guarantee does not imply that they comply with their SLAs. Many reports addressed that CSPs' downtime is much greater and usually the cloud consumer's costs cannot be covered by CSP's indemnification. On the other hand, the service availability is not a decisive factor for many cloud consumers. That is, many cloud consumers are interested in lower cost for an acceptable level of availability. In this paper, we define a new methodology to evaluate the CSPs according to the cloud consumers' needs. We introduce a very important factor, i.e., trustworthiness beside the availability. With our methodology, the cloud consumers can quantify the trustworthiness and the security of their potential CSPs, in order to migrate their services to the most appropriate CSP. Our evaluation shows that Google is the best choice of the evaluated CSPs in trustworthiness, although it offers the worst availability in its SLA, compared to other most common CSPs.
ffectiveness of Gait Training Using an Electromechanical ait Trainer , With and Without Functional Electric timulation , in Subacute Stroke : A Randomized ontrolled Trial

Objective: To compare the therapeutic effects of convenional gait training (CGT), gait training using an electromehanical gait trainer (EGT), and gait training using an electroechanical gait trainer with functional electric stimulation EGT-FES) in people with subacute stroke. Design: Nonblinded randomized controlled trial. Setting: Rehabilitation hospital for adults. Participants: Fifty patients were recruited within 6 weeks fter stroke onset; 46 of these completed the 4-week training eriod. Intervention: Participants were randomly assigned to 1 of 3 ait intervention groups: CGT, EGT, or EGT-FES. The expermental intervention was a 20-minute session per day, 5 days a eek (weekdays) for 4 weeks. In addition, all participants eceived their 40-minute sessions of regular physical therapy very weekday as part of their treatment by the hospital. Main Outcome Measures: Five-meter walking speed test, lderly Mobility Scale (EMS), Berg Balance Scale, Functional mbulatory Category (FAC), Motricity Index leg subscale, IM instrument score, and Barthel Index. Results: The EGT and EGT-FES groups had statistically ignificantly more improvement than the CGT group in the 5-m alking speed test (CGT vs EGT, P .011; CGT vs EGT-FES, .001), Motricity Index (CGT vs EGT-FES, P .011), EMS CGT vs EGT, P . 006; CGT vs EGT-FES, P . 009), and FAC CGT vs EGT, P . 005; CGT vs EGT-FES, P . 002) after the weeks of training. No statistically significant differences ere found between the EGT and EGT-FES groups in all utcome measures. Conclusions: In this sample with subacute stroke, particiants who trained on the electromechanical gait trainer with ody-weight support, with or without FES, had a faster gait,
Existence and regularity results for solutions to nonlinear parabolic equations

In this paper we prove some existence and regularity results for weak solutions to a class of nonlinear parabolic equations whose prototype is  ∂u ∂t −∆pu = f(x, t) in Q, u(x, 0) = 0 in Ω, u(x, t) = 0 on Γ, where Ω is a bounded open subset of IR , N ≥ 2, Q is the cylinder Ω×]0, T [, T > 0, Γ the lateral surface ∂Ω×]0, T [, 4p is the so called p−Laplace operator, 1 < p < N and f belongs to some space Lr(0, T ;Lq(Ω)), r ≥ 1, q ≥ 1.
Learning-based power prediction for data centre operations via deep neural networks

Modelling and analyzing power consumption for data centres can diagnose potential energy-hungry components and applications, and facilitate in-time control, benefiting the energy efficiency of data centers. However, solutions to this problem, including static power models and canonical prediction models, either aim to build a static relationship between power consumption and hardware/application configurations without considering the dynamic fluctuation of power; or simply treat it as time series, ignoring the inherit power data characteristics. To tackle these issues, in this paper, we present a systematic power prediction framework based on extensive power dynamic profiling and deep learning models. In particular, we first analyse different power series samples to illustrate their noise patterns; accordingly we propose a power data de-noising method, which lowers noise interference to the modelling. With the pretreated data, we propose two deep learning based prediction models, including a fine-grained model and a coarse-grained model, which are suitable for different time scales. In the fine-grained prediction model, a recursive autoencoder (AE) is employed for short-duration prediction; in the coarse-grained model, an AE is used to encode massive fine-grained historical data as a further data pretreatment for long-duration prediction. Experimental results show that our proposed models outperform canonical prediction methods with higher accuracy, up to 79% error reduction for certain cases.
Software Development Effort Estimation: Formal Models or Expert Judgment?

Which is better for estimating software project resources: formal models, as instantiated in estimation tools, or expert judgment? Two luminaries, debate this question in this paper. For this debate, they're taking opposite sides and trying to help software project managers figure out when, and under what conditions, each method would be best.
Performance evaluation of UDP-based high-speed transport protocols

The emergence of high speed long distance networks has promoted the development of various e-science applications. The traditional TCP protocol is not suitable for high bandwidth-delay product networks because of its conservative Additive Increase Multiplicative Decrease (AIMD) congestion control algorithm and slow start strategy. This paper mainly introduces four kinds of typical UDP-based high speed transport protocols (RUBDP, Tsunami, UDT, and PA-UDP). By experiments on the test bed with end-to-end transport mode, the influence of the file size, loss ratio and RTT to the performance of the four protocols is evaluated. And, the intra-protocol fairness and inter-protocol fairness while transferring multiple parallel flows are also evaluated. The results show: PA-UDP protocol has the best transport performance; UDT protocol is the most convenient, because it does not require the users to set the initial sending rate, buffer size and other parameters.
Four meanings of “categorization”: A conceptual analysis of research on person perception

It is widely assumed that people tend to “categorize” other people. However, the term “categorization” has been used with qualitatively different underlying definitions in the person perception literature. We present a conceptual analysis in which we disentangle four existing definitions: (a) categorization as representing, (b) categorization as dichotomizing, (c) categorization as organizing, and (d) categorization as grouping. Subsequently, we show that seemingly antagonistic viewpoints in the literature may be reconciled by disentangling these definitions. Furthermore, we argue that disentangling these definitions is vital for theoretical interpretations of (past and future) empirical findings. Overall, our work aims to contribute to the clarity of person perception theories, provide novel perspectives on existing debates, and serve as a stepping stone for more differentiated models of person perception.
Analysis of Recent Studies Undertaken for Assessing Acceptance of Technology among Teachers using TAM

Although there is an increase in availability and support for technology integrated teaching and learning methods , teachers‘ acceptance of technology into their teaching activities seems very low. The study aims at probing recent usage of the Technology Acceptance Model (TAM), in assessing acceptance of technology among teachers from among the research publications with a focus on behavior intentions of teachers towards technology adoption and usage, published in peer reviewed journals and conference proceedings 2005 onwards. The analysis projects TAM as a robust model which can be used in assessing technology acceptance among teachers, in the educational vertical, just as it has been used in various business verticals. The review provides evidences that TAM can predict actual usage by using both subjective and objective measures.
Integrated Software Architecture Management and Validation

Many software projects suffer from problems related to non-existent, incomplete, inaccurate, or invalid architecture descriptions. The hypothesis underlying our approach is that architecture related activities, notations, and artifacts are not integrated well enough with the development process,with the development tools and, in particular, with the implementation of a software system. We present an approach in which we emphasize the architectural description of a system as a central element during the whole software development process. The main idea is to incorporate a formalized architecture description model into a software system which is always kept up-to-date during software development. A toolkit, which is based on the model, is used for continuously defining, validating, visualizing and evolving the architecture during development.
Melatonin Regulates Root Meristem by Repressing Auxin Synthesis and Polar Auxin Transport in Arabidopsis

Melatonin (N-acetyl-5-methoxytryptamine) plays important roles in regulating both biotic and abiotic stress tolerance, biological rhythms, plant growth and development. Sharing the same substrate (tryptophan) for the biosynthesis, melatonin and auxin also have similar effects in plant development. However, the specific function of melatonin in modulating plant root growth and the relationship between melatonin and auxin as well as underlying mechanisms are still unclear. In this study, we found high concentration of melatonin remarkably inhibited root growth in Arabidopsis by reducing root meristem size. Further studies showed that melatonin negatively regulated auxin biosynthesis, the expression of PINFORMED (PIN) proteins as well as auxin response in Arabidopsis. Moreover, the root growth of the triple mutant pin1pin3pin7 was more tolerant than that of wild-type in response to melatonin treatment, suggesting the essential role of PIN1/3/7 in melatonin-mediated root growth. Combination treatment of melatonin and 5-Triiodobenzoic acid (TIBA) did not enhance melatonin-mediated reduction of root meristem size, indicating that polar auxin transport (PAT) may be necessary for the regulation of root meristem size by melatonin treatment. Taken together, this study indicates that melatonin regulates root growth in Arabidopsis, through auxin synthesis and polar auxin transport, at least partially.
PALI: a database of alignments and phylogeny of homologous protein structures

PALI is a database of structure-based sequence alignments and phylogenetic relationships derived on the basis of three-dimensional structures of homologous proteins. This database enables grouping of pairs of homologous protein structures on the basis of their sequence identity calculated from the structure-based alignment and PALI also enables association of a new sequence to a family and automatic generation of a dendrogram combining the query sequence and homologous protein structures.
Excessive Noise Injection Training of Neural Networks for Markerless Tracking in Obscured and Segmented Environments

In this letter, we demonstrate that the generalization properties of a neural network (NN) can be extended to encompass objects that obscure or segment the original image in its foreground or background. We achieve this by piloting an extension of the noise injection training technique, which we term excessive noise injection (ENI), on a simple feedforward multilayer perceptron (MLP) network with vanilla backward error propagation to achieve this aim. Six tests are reported that show the ability of an NN to distinguish six similar states of motion of a simplified human figure that has become obscured by moving vertical and horizontal bars and random blocks for different levels of obscuration. Four more extensive tests are then reported to determine the bounds of the technique. The results from the ENI network were compared to results from the same NN trained on clean states only. The results pilot strong evidence that it is possible to track a human subject behind objects using this technique, and thus this technique lends itself to a real-time markerless tracking system from a single video stream.
What do You Mean? Finding Answers to Complex Questions

This paper illustrates ongoing research and issues faced when dealing with real-time questions in the domain of Reusable Launch Vehicles (aerospace engineering). The question-answering system described in this paper is used in a collaborative learning environment with real users and live questions. The paper describes an analysis of these more complex questions as well as research to include the user in the question-answering process by implementing a question negotiation module based on the traditional reference interview.
Homogenization of Parabolic Equations with a Continuum of Space and Time Scales

This paper addresses the issue of the homogenization of linear divergence form parabolic operators in situations where no ergodicity and no scale separation in time or space are available. Namely, we consider divergence form linear parabolic operators in $\Omega \subset \mathbb{R}^n$ with $L^\infty(\Omega \times (0,T))$-coefficients. It appears that the inverse operator maps the unit ball of $L^2(\Omega\times (0,T))$ into a space of functions which at small (time and space) scales are close in $H^1$ norm to a functional space of dimension $n$. It follows that once one has solved these equations at least $n$ times it is possible to homogenize them both in space and in time, reducing the number of operation counts necessary to obtain further solutions. In practice we show under a Cordes-type condition that the first order time derivatives and second order space derivatives of the solution of these operators with respect to caloric coordinates are in $L^2$ (instead of $H^{-1}$ with Euclidean coordinates). If the medium is time-independent, then it is sufficient to solve $n$ times the associated elliptic equation in order to homogenize the parabolic equation.
Reliability and Validity of the Persian Version of Compulsive Eating Scale (CES) in Overweight or Obese Women and Its Relationship with Some Body Composition and Dietary Intake Variables

Objective: Compulsive or binge eating is a kind of disturbed eating behavior, which is mostly observed among dieting women, and is integrated with appetite disorder, and uncontrolled eating of plenty of junk food. The Compulsive Eating Scale (CES) created first by Kagan & Squires in 1984, is an eight-item self-reporting instrument that is made to measure the severity of binge eating disorder. The aim of this study was to provide the reliability and validity of the Persian version of Compulsive Eating Scale (CES) among overweight and obese women in Iran. Method: One hundred and twenty six (N = 126) overweight and obese women consented to participate in this study. We estimated the anthropometric indices, including body weight, height, waist and hip circumferences, a total body fat percentage, and visceral fat level with body analyzer all in standard situations. Then, the participants completed the CES. Next, to assess concurrent validity, Beck Depression Inventory, Spielberger anxiety scale, appetite visual analogue rating scale, Food Craving questionnaire, Three-Factor Eating Questionnaire-R18, and Restraint eating visual analogue rating scale were performed simultaneously. To assess test-retest reliability, CES was repeated for all the participants two weeks later. Moreover, we reported the internal consistency and factor analysis of this questionnaire. Furthermore, we estimated the concurrent correlation of CES with logically relevant questionnaires and body composition and anthropometric indices. Results: Based on the reliability analysis and factor analysis of the principal component by Varimax rotation, we extracted two factors: eating because of negative feelings, and overeating. Internal consistency (Cronbach's alpha) of the CES was 0.85 (Cronbach alpha of the factors was 0.85, and 0.74, respectively). The test-retest correlation of the CES was 0.89. Also, the split-half reliability of the questionnaire was established with the correlation coefficient between Sets I and II. The correlation was 0.85. Conclusion: This study provides preliminary support for the reliability and validity of the Persian version of the CES. This instrument would be helpful in measuring the clinical practice and research studies of obesity, appetite and eating disorders reliably and validly.
Sentiment classification of online product reviews using product features

There is a great number of online product reviews on the Internet which needs to be organized. In this paper, we consider the problem of sentiment classification of online reviews to determine the overall semantic orientation of customer reviews. Our proposed method for review classification is a supervised machine learning method based on extracting product features and the polarity of opinions expressed about the features.
SCY-078 Is Fungicidal against Candida Species in Time-Kill Studies

ABSTRACT SCY-078 is an orally bioavailable ß-1,3-glucan synthesis inhibitor (GSI) and the first-in-class of structurally novel triterpene antifungals in clinical development for treating candidemia and invasive candidiasis. In vitro susceptibilities by broth microdilution, antifungal carryover, and time-kill dynamics were determined for three reference (ATCC) strains (Candida albicans 90028, Candida parapsilosis 90018, and Candida tropicalis 750), a quality-control (QC) strain (Candida krusei 6258), and four other strains (C. albicans MYA-2732, 64124, and 76485 and Candida glabrata 90030). Caspofungin (CASP), fluconazole (FLC), and voriconazole (VRC) were comparators. For time-kill experiments, SCY-078 and CASP were evaluated at 0.25, 1, 2, 4, 8, and 16 times the MIC80, and FLU and VRC were evaluated at 4× MIC80. The time to reach 50%, 90%, and 99.9% reduction in the number of CFUs from the starting inoculum was determined. Net change in the number of CFU per milliliter was used to determine 50% and 90% effective concentrations and maximum effect (EC50, EC90, and Emax, respectively). The SCY-078 MIC range was between 0.0625 and 1 μg/ml and generally similar to that of CASP. Antifungal carryover was not observed for SCY-078. SCY-078 was fungicidal against seven isolates at ≥4× MIC (kill of ≥3 log10) and achieved a 1.7-log10 reduction in CFU count/milliliter against C. albicans 90028. CASP behaved similarly against each isolate and achieved a 1.5-log10 reduction in the number of CFU/milliliter against C. albicans 90028. Reductions of 50% in CFU count/milliliter were achieved rapidly (1 to 2.8 h); fungicidal endpoints were reached at 12.1 to 21.8 h at ≥4× MIC. EC90 was reached at ∼5× MIC at each time point to 24 h. The EC50 and EC90 values were generally similar (8 to 24 h). Time-kill behavior of CASP was similar to that of SCY-078. FLC and VRC were fungistatic. Overall, SCY-078 has primarily fungicidal activity against Candida spp. and behaved comparably to CASP.
A closed-loop selective harmonic compensation for active filters

This paper proposes a control algorithm for parallel active power filters, based on current-controlled PWM converters, which allows precise compensation of selected harmonic currents produced by distorting loads. The approach is based on the measurement of line currents and performs the compensation of the selected harmonics using closed-loop synchronous frame controllers. Because of the closed-loop operation, full compensation of the desired harmonics is achieved even in the presence of a significant delay in the VSI current control. Because of the selective approach, active filter interactions with a possible dynamic component of the load are minimized. The complexity of the synchronous frame controllers are avoided using equivalent stationary frame controllers with the same dynamic performance. Experimental results of a converter prototype confirm the theoretical expectations.
Identification of Chinese Event and Their Argument Roles

Event detection and recognition is a major task in ACE evaluation plan. In this paper, we focus on solving the two subtasks: (1) event detection and classification, (2) their argument role identification. For the first subtask, the strategy of local feature selection and explicit discrimination of positive and negative features is used in order to ensure the performance of each type. For the second subtask, the approach based on multi-level patterns is presented in order to improve the coverage of patterns and to use various language information. Experiments on the ACE2005 corpus show that performance of the first subtask is satisfying with the 83.5% macro-average F1-measure. And experiments of the second subtask show that the method based on multi-level patterns is very promising.
Deep analysis of knowledge in one's writings

Reading the opinion behind the text is a big challenge. In another way, we need to automatically read opinions and moods as a natural language. Ontology -based plays a main role to solve the problems in this field. That is from the features of the ontology based as covering the semantics of the concepts. So, in this paper, we propose a flexible classification opinion mining tool. This proposed method based on ontology- based. The proposed method uses NLTK (Natural Language Processing Toolkit) with Python as a useful knowledge to get more representative word occurrences in the corpus. Also, we not only use a WordNet and SentiWordNet ontologies to assign the word as POS (part of speech), but we also create a specific purpose ontology by OWL editor as Protégé. Then we create a more general opinion mining tool where the specific purpose ontology file was selected to use for classification the text. We apply our proposed method on lists of long texts for different writers, and then we can classify these writers depending on their writings.