Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase I trial of interleukin-12 plasmid electroporation in patients with metastatic melanoma.

PURPOSE Gene-based immunotherapy for cancer is limited by the lack of safe, efficient, reproducible, and titratable delivery methods. Direct injection of DNA into tissue, although safer than viral vectors, suffers from low gene transfer efficiency. In vivo electroporation, in preclinical models, significantly enhances gene transfer efficiency while retaining the safety advantages of plasmid DNA. PATIENTS AND METHODS A phase I dose escalation trial of plasmid interleukin (IL)-12 electroporation was carried out in patients with metastatic melanoma. Patients received electroporation on days 1, 5, and 8 during a single 39-day cycle, into metastatic melanoma lesions with six 100-mus pulses at a 1,300-V/cm electric field through a penetrating six-electrode array immediately after DNA injection. Pre- and post-treatment biopsies were obtained at defined time points for detailed histologic evaluation and determination of IL-12 protein levels. RESULTS Twenty-four patients were treated at seven dose levels, with minimal systemic toxicity. Transient pain after electroporation was the major adverse effect. Post-treatment biopsies showed plasmid dose proportional increases in IL-12 protein levels as well as marked tumor necrosis and lymphocytic infiltrate. Two (10%) of 19 patients with nonelectroporated distant lesions and no other systemic therapy showed complete regression of all metastases, whereas eight additional patients (42%) showed disease stabilization or partial response. CONCLUSION This report describes the first human trial, to our knowledge, of gene transfer utilizing in vivo DNA electroporation. The results indicated this modality to be safe, effective, reproducible, and titratable.
Decision Criteria in the Adoption of EDI

Electronic data interchange, or EDI, has been discussed in literature as a technology that can provide a strategic advantage to its adopters, like other interorganizational information systems. However, its actual rate of adoption is nowhere near the predictions. Authors are now reconsidering their assessment of EDI's advantages and its role in organizations' strategies. However, using works found in critical mass theory, and through results gathered with the survey, case study and computer-supported interviews, this paper shows that organizations are acting strategically when deciding to not adopt EDI. They base their decisions on what their business partners are doing with respect to EDI, and on whether the actual and potential businesses they represent justify the investment required in EDI. The implications of the results for the study of innovation diffusion are discussed.
Qualitative Research on the Impact of Information and Communication Technology on Penang Port Sdn. Bhd

The use of (ICT) in logistics has been advocated to enhance the performance of the logistics sector especially in the seaports. A huge number of researches showed the importance of using RBV in analyzing performance. RBV however has been adopted in accordance to address the implication of IT on performance for many years, and the latest findings on “IT-performance” relationship is very unclear to make a conclusion. Therefore, further study on application of this theory in the ICT-performance relationship in port industry. This study seeks to examine the impact of ICT implementation on Penang Port Sdn. Bhd. (PPSB) performance. This research is exploratory in nature and the data was collected through a series of interviews. The result from this study shows that there are impact on the ICT usage, container management and Smart-Rail system on port performance. However, this study indicates that port security system does not give an impact towards achieving overall port performance. This study found that technology resources raise internal and external capabilities, which in turn affect port performance. Port resources positively affect organizational efficiency through its impact on internal capabilities thus directly impact the port performance. The results of this study provide direction for investing and managing organizational it resources to achieve competiveness.
Thermal imaging bundle - A potential tool to enhance minimally invasive medical procedures

IEEE CIRCUITS & DEVICES MAGAZINE ■ NOVEMBER/DECEMBER 2005 8755-3996/05/$20.00 ©2005 IEEE T he growing importance of infrared (IR) imaging in medicine, along with improvements in thermal imaging camera technology, is triggering the development of coherent bundles from different materials transparent in the IR spectral range. Efforts to develop practical, biocompatible, high-resolution, long and flexible thermal imaging bundles are described in this article. The aim is to replicate the success of the imaging bundles in the visible range that modern medicine cannot live without.
Dose-response modeling with bivariate binary data under model uncertainty

When modeling a dose-response for a drug based on bivariate binary data such as two co-primary efficacy endpoints in early stages of development, there is usually uncertainty about the from of the true underlying dose-response shape. Often, investigators fit several different models that are deemed plausible, but later fail to acknowledge this uncertainty in inference that is based on a single model selected via e.g. the minimum AIC criterion. This leads to an inflation in the error of the proof of activity decision and may also result in poor estimation of a target dose that is used in future trials. In this article we acknowledge model uncertainty by fitting several candidate models for a bivariate binary response and develop a principled approach to establish proof of activity and a target dose.
Bio-inspired Data Placement in Peer-to-Peer Networks - Benefits of using Multi-agents Systems

In this paper we present the benefits of using a multi-agents system to manage the data placement in a decentralized storage application. In our model, after a fragmentation step, each piece of data is associated to a mobile agent making its own decisions. To manage agents placement, we apply flocking rules in a peer-to-peer network called SCAMP. Each agent follows simple rules and the emerging behavior is a flock of fragments. To provide an efficient load-balancing, agents drop pheromones among network peers. We made some experiments to measure the cohesion degree of our flock and to measure the network coverage of a flock. We also discuss about availability and reliability of our approach.
Experimental design and analysis and their reporting: new guidance for publication in BJP

This Editorial is part of a series. To view the other Editorials in this series, visit: http://onlinelibrary.wiley. com/doi/10.1111/bph.12956/abstract; http://onlinelibrary.wiley. com/doi/10.1111/bph.12954/abstract; http://onlinelibrary.wiley. com/doi/10.1111/bph.12955/abstract and http://onlinelibrary.wiley. com/doi/10.1111/bph.13112/abstract
Representing word image using visual word embeddings and RNN for keyword spotting on historical document images

Visual words of Bag-of-Visual-Words (BoVW) framework are independent each other, which results in not only discarding spatial orders between visual words but also lacking semantic information. This study is inspired by word embeddings that a similar embedding procedure is applied to a large number of visual words. By this way, the corresponding embedding vectors of the visual words can be formulated. For a word image, the average of embedding vectors of all visual words within the word image is taken as its embedding vector. Moreover, Recurrent Neural Network (RNN) is utilized to encode each word image into embeddings like an auto-encoder. The RNN embeddings and the visual word embeddings are complementary. In this study, all word images are represented by combining visual word embeddings and RNN embeddings. Experimental results show that the proposed representation approach is superior to the traditional BoVW, spatial pyramid matching and latent Dirichlet allocation.
Effect of leadership style and organizational climate on employees' food safety and hygiene behaviors in the institutional food service of schools

Abstract This study took the employees working in the institutional food service of schools in northern Taiwan as subjects to explore the influences of leadership style and organizational climate on food safety and hygiene behaviors. In this study, 400 questionnaires were distributed and 324 valid questionnaires were collected, for a valid return rate of 81%. The results showed that leadership style and organizational climate positively correlate with employees' behaviors with respect to food safety and hygiene. Transactional and transformational leadership have a significantly positive effect on organizational climate. Organizational climate has a significantly positive impact on employees' food safety and hygiene behaviors. Transactional and transformational leadership have a significantly positive effect on employees' food safety and hygiene behaviors, but the difference between the two factors is not obvious. Organizational climate has a complete mediating effect on the process of transactional and transformational leadership affecting food safety and hygiene behaviors.
Implications of climate mitigation for future agricultural production

Climate change is projected to negatively impact biophysical agricultural productivity in much of the world. Actions taken to reduce greenhouse gas emissions and mitigate future climate changes, are thus of central importance for agricultural production. Climate impacts are, however, not unidirectional; some crops in some regions (primarily higher latitudes) are projected to benefit, particularly if increased atmospheric carbon dioxide is assumed to strongly increase crop productivity at large spatial and temporal scales. Climate mitigation measures that are implemented by reducing atmospheric carbon dioxide concentrations lead to reductions both in the strength of climate change and in the benefits of carbon dioxide fertilization. Consequently, analysis of the effects of climate mitigation on agricultural productivity must address not only regions for which mitigation is likely to reduce or even reverse climate damages. There are also regions that are likely to see increased crop yields due to climate change, which may lose these added potentials under mitigation action. Comparing data from the most comprehensive archive of crop yield projections publicly available, we find that climate mitigation leads to overall benefits from avoided damages at the global scale and especially in many regions that are already at risk of food insecurity today. Ignoring controversial carbon dioxide fertilization effects on crop productivity, we find that for the median projection aggressive mitigation could eliminate ∼81% of the negative impacts of climate change on biophysical agricultural productivity globally by the end of the century. In this case, the benefits of mitigation typically extend well into temperate regions, but vary by crop and underlying climate model projections. Should large benefits to crop yields from carbon dioxide fertilization be realized, the effects of mitigation become much more mixed, though still positive globally and beneficial in many food insecure countries.
Antecedents of Online Customers Reviews' Helpfulness: A Support Vector Machine Approach

Online customer reviews (OCRs) have become an important part of online customers’ decision making and People use online reviews to make decision to buy or not to buy products and services. This study aims to answer two research questions: (1) what are the antecedents of helpfulness of online reviews based on their contents? (2) How do content-based cues on OCRs influence their helpfulness? We posit a research model to study the effect of peripheral and central cues in OCRs on online review helpfulness. Online review web pages will be collected from Amazon website using a web crawler. This article will be one of the first studies that investigate OCRs helpfulness based on the central cues in the text of the review. In addition, this research will be the first study that applied the support vector machine as a machine learning method to analyze the text of OCRs.
Cleavage rate of haploid and diploid parthenogenetic mouse embryos during the preimplantation period

The lack of a paternal genome in parthenogenetic embryos clearly limits their postimplantation development, but apparently not their preimplantation development, since morphologically normal blastocysts can be formed. The cleavage rate of these embryos during the preimplantation period gives a better indication of the influence of their genetic constitution than blastocyst formation. Conflicting results from previous studies prompted us to use a more suitable method of following the development of haploid and diploid parthenogenetic embryos during this period.
Novel Consumer Classification Scheme for Smart Grids

Classifying different type of consumers (households, office buildings and industrial plants) is an important task in Smart Grids. In this paper, we propose a novel classification scheme based on nonlinear prediction for consumption timeseries obtained from a smart meter. The candidate predictors were tested under different assumptions regarding the statistical behavior of the underlying consumption time-series. As a result a feedforward neural network based predictor has been shown to be the most promising solution. In order to demonstrate the power of the proposed method simulations have been carried out. The consumption data came from a bottom up model, where Markov model of individual appliances and real measurements of photo-voltaic generators have been applied. The numerical results prove that our method is capable of distinguishing an office-building with installed photo voltaic mini power plant from an office-building which is lack of such power plant.
Improving the precision of RSSI-based low-energy localization using path loss exponent estimation

In this paper we present a method for improving the precision of an RSSI-based energy-constrained localization system employed in an IEEE 802.15. 4 sensor network. The goal application is localization of people in dynamic indoor environments. We introduce an approach which divides the anchor nodes into groups and assigns a path loss exponent to each group. The results from the conveyed tests in our building show a location error smaller than 3m, despite the low energy constraints. Moreover, we provide a hardware platform independent system suitable for both standard and proprietary solutions.
Adaptive computer assisted assessment of free-text students' answers: an approach to automatically generate students' conceptual models

Los profesores intentan transmitir su conocimiento a los estudiantes para que adquieran los conceptos a compartir por la comunidad, Sin embargo, lo que cada estudiante comprende puede ser muy distinto. Esto es, porque cada estudiante construye su propio modelo conceptual como una red de conceptos interrelacionados dependiendo de su bagaje particular. Ademas, segun la teoria del aprendizaje significativo de Ausubel, para poder aprender nuevos conceptos es necesario tener unos conceptos previos con los que enlazarlos. Los sistemas tutores inteligentes (ITS) son un tipo de software educativo que contiene un modelo sobre el estudiante y que se adaptan a su ritmo de aprendizaje. Los sistemas Hipermedia Adaptativos para la educacion (HAE) estan inspirados en los ITS para adaptar el contenido y la navegacion en un curso al modelo de estudiante. Sin embargo, la evaluacion de estos sistemas se limita a preguntas cerradas, que segun la opinion de los expertos en evaluacion no pueden identificar muchos de los errores conceptuales de los estudiantes. Por lo tanto, la evaluacion automatica de preguntas abiertas es un campo que se esta estudiando bastante y que se basa en usar tecnicas de Procesamiento del Lenguaje Natural (PLN). En la actualidad, existen alrededor de unos 20 sistemas de este tipo, pero ninguno usa un modelo de estudiante. Se ha destacado la importancia de mantener un modelo del estudiante que sirva para identificar la falta de conocimiento previo y permitir que el sistema decida que preguntas son las mas adecuadas. Por lo tanto, en este trabajo, se han combinado ideas de los campos de PLN, HAE y evaluacion de respuestas en texto libre para construir un puente entre lo que los profesores intentan transmitir en sus clases y lo que los estudiantes comprenden. Este objetivo se cumple mediante un nuevo procedimiento capaz de generar de forma automatica los modelos conceptuales de los estudiantes a partir de sus respuestas a un sistema automatico
Children's susceptibility to retroactive interference: the effects of age and degree of learning.

The effects of age and degree of learning on children's susceptibility to retroactive interference were examined. Children (4- and 7-year-olds) participated in a target game either once or three times. Each time, they learned the target stimuli to criterion. Two days later, the children either rested or participated in a second game containing inconsistent information. Retrieval tests were administered 3 weeks later. Children who participated in the target game repeatedly recognized more information from that game, both accurately and as intrusions, than did children who participated only once. Both age groups were susceptible to retroactive interference; degree of susceptibility was affected by neither age nor degree of learning. Nevertheless, the 7-year-olds were more accurate at test. These findings suggest that differences in the forgetting rate between 4- and 7-year-olds are not caused by differential susceptibility to retroactive interference.
Sharp interface limit for the Cahn-Larché system

We prove rigorously the convergence of the Cahn-Larch\'e system, which is a Cahn-Hilliard system coupled with the system of linearized elasticity, to a modified Hele-Shaw problem as long as a classical solution of the latter system exists. By matched asymptotic expansion we construct approximate solutions and estimate the difference between the true and the approximate solutions.
Using Rich Inference to Find Novel Answers to Questions

The Web is continuously enriched with data and has become a large knowledge repository. However, machines are unable to fully exploit this vast knowledge space in performing reasoning tasks such as question answering. This inability limits the extent of inference and ultimately limits the range of questions they can answer. We argue that the quality and range of answers generated by a question-answering system is significantly improved when we use rich reasoning techniques to infer novel knowledge from web data. By finding and aggregating facts from different knowledge bases, an agent can obtain a better representation of a domain and hence infer new facts which did not exist in any of the original knowledge sources. We intend to explore rich semantic representations and rich forms of reasoning. These include the curation of data and the use of a combination of heuristics, logic and probabilistic techniques to infer answers. This approach will minimize noise and uncertainty in the knowledge for reasoning. Our customized representations will suit the problem to be solved rather than being restricted by the formalisms used in the sources. We plan to implement this in a question-answering system that exploits a vast set of knowledge bases such as ontologies and Linked Data repositories. Our question-answering system will focus on questions which require rich inferences such as prediction and composition of answers from several pieces of information. Keywords— inference, question-answering, knowledge representation, heuristics, uncertainty
Delta–Sigma Encoder for Low-Power Wireless Bio-Sensors Using Ultrawideband Impulse Radio

This brief presents a systematic method to reduce the power consumption of a wireless sensor node for sensing biomedical signals. The design combines the delta–sigma modulator (DSM), the ultrawideband impulse radio (UWB-IR), and the proposed xnor-delay-based encoder/decoder, which replaces the decimation filter. The encoder and decoder for both the first- and second-order DSMs are presented. The clock synchronization problem is solved by using an asynchronous UWB-IR. The effects of window length, the order of delta–sigma modulation, and the oversampling ratio are studied by simulation using neural and electrocardiography signals. Based on the simulation results, the proposed method can save power by 50% compared to the system with decimation filters, and 53% compared to the system without the proposed encoder.
Hyper-patches for 3D model acquisition and tracking

Automatic 3D model acquisition and 3D tracking of simple objects under motion using a single camera is often difficult due to the sparsity of information from which to establish the model. We have developed an automatic scheme that first computes a simple pointalistic Euclidean model of the object and then enriches this model using hyper-patches. These hyper-patches contain information on both the orientation and intensity pattern variation of roughly planar patches on an object. This information allows both the spatial and intensity distortions of the projected patch to be modelled accurately under 3D object motion. We show that hyper-patches not only can be computed automatically during model acquisition from a monocular image sequence, but that they are also extremely appropriate for the task of visual tracking.
Follow-Up of Patients with Breast Cancer : Role of Breast MRI in the Early Detection of New Breast Tumors ( on the Basis of Two Cases )

Background: Breast Magnetic Resonance Imaging (MRI) follows up is recommended in women at high risk (either genetic risk or family history) of breast cancer. However, its use is not extended in the case of patients with personal history of breast cancer, although this is a risk factor for new malignant breast tumors. We present two cases diagnosed only by MRI in patients with a history of breast cancer. Method: Two cases of patients with a personal history of breast cancer underwent both mammography and breast ultrasound as follow up are presented. Results: Two patients of 38 and 42 years of age diagnosed of unilateral breast cancer 3 and 7 years ago, respectively. Both of them were clinically asymptomatic and follow up in their health centers only by mammography in case 1 and with both mammography and breast ultrasound in case 2, being reported as without pathological findings. In both cases, only the breast MRI allowed to diagnose a new tumor in the contralateral breast. Conclusions: In the follow up of patients with a personal history of breast cancer, breast MRI allows the detection of non-visualized tumors with routine mammographic and breast ultrasound controls. Therefore, we recommend its use along with mammography, especially if they have undergone reconstructive surgery.