Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in Intraocular Pressure during Prolonged (7-Day) Head-Down Tilt Bedrest

PurposeTo determine the change in intraocular pressure (IOP) due to postural changes in young healthy volunteers. Materials and MethodsIntraocular pressure was measured using a calibrated Pulsair noncontact tonometer in both eyes of 25 female volunteers in a sitting position and after 1, 3, and 10 minutes in a supine position. In the second part of the experiment (a 7-day −6° head-down tilt [HDT]), IOP (at 8 am, 12 am and 6 pm) and corneal thickness (12 am) were monitored in 8 female volunteers before, during, and after the HDT period. Blood pressure, hematocrit, plasma volume and osmolality, and plasma catecholamines concentrations were also measured. ResultsIntraocular pressure was significantly higher in the supine position (16.1 ± 3.6 mm Hg) than in the sitting position, with a mean pressure difference of 2.23 ± 2.9 mm Hg after 1 minute, 0.9 ± 3 mm Hg after 3 minutes, and 1.9 ± 3.8 mm Hg after 10 minutes in a supine position (P < 0.001). During the period of HDT, IOP values decreased significantly on the fifth day (13.3 ± 1.6 mm Hg, P = 0.03) and the seventh day (12.7 ± 1.7 mm Hg, P = 0.02) when compared with IOP in the supine position (14.26 ± 2 mm Hg). The corneal thickness increased significantly (P < 0.0001) at day 5 (549.25 ± 48.7 &mgr;m) and day 7 (540.31 ± 46.9 &mgr;m) compared with baseline (532.45 ± 38.6 &mgr;m). Two days after the end of the HDT bedrest, the mean supine IOP significantly increased (14.1 ± 1.8 mm Hg, P = 0.003) and corneal thickness was similar to that found at baseline. The mean decrease of IOP was positively correlated with that of the plasma volume (−10%, r = 0.61, P = 0.02) and negatively correlated with the mean rise of hematocrit (r = −0.5, P = 0.07), variables that are considered to be indirect measures of plasma dehydration. ConclusionsDuring a 7-day HDT bedrest experiment in healthy women, eyes seemed to compensate the moderate rise of IOP described between a sitting and a supine position, and exhibited a slight and progressive average decrease of 1.3 mm Hg. These physiological modifications could be related to an ocular dehydration or to systemic cardiovascular and hormonal variations during bedrest.
On Information Disclosure of Listed Companies through New Media:An Empirical Analysis Based on Microblog

In recent years, new media like microblog plays a more and more important role in public information sharing and communication.The emergence of new media on the internet not only creates a new mode of interpersonal communication, but also brings significant impact and change to information provision & communication and approaches, routes& timeliness of information acquisition on the capital market.Through hand collecting and detailed reading of information of listed companies published on Sina microblog, this paper investigates microblog information disclosure of listed companies for the first time.Results show that the content of information disclosed by listed companies through microblog is very extensive, and the most content of information disclosed is operation information, especially sales contracts, awards and R&D & innovation.Besides, about 84% of the information disclosed by listed companies through microblog is not published through official announcements.Furthermore, it also examines the effects of the characteristics of listed companies on their willingness to register in Sina microblog and the number of released information.Results show that companies with high-level corporate governance more tend to register in Sina microblog and release more information closely related to the companies, especially information that is not published through official announcements and strategy-based information about operation activities.Information disclosure through new media on the internet as an emerging field is worthy of deep study on issues like how information disclosure through new media on the internet affects listed companies and whether it can reduce the stock price synchronicity and the financing costs.
Prediction of NOx emissions from a biomass fired combustion process through digital imaging, non-negative matrix factorization and fast sparse regression

This paper presents the development and evaluation of an algorithm for the prediction of NOx emissions from a biomass fired combustion process based on flame radical imaging, image processing and soft computing techniques. The investigation was performed on a biomass-gas fired test rig. An algorithm which combines texture analysis and non-negative matrix factorization (NMF) is studied for the image feature extraction. Fast sparse regression with convex penalties is then employed to establish the relationship between the image features and NOx emissions. The predicted NOx emissions from a fitted model are in good agreement with the measurement results. The results demonstrate that the proposed technical approach to the prediction of NOx emissions is effective.
Resolución sumergida de foliaciones sobre el plano proyectivo complejo

EN LA PRIMERA PARTE DEL TRABAJO SE ESTUDIA, DADO UN HAZ DE MODULOS LOCALMENTE LIBRE DE RANGO N SOBRE UN ESQUEMA INTEGRO, NOETHERIANO Y LOCALMENTE FACTORIAL, LA RELACION ENTRE SUBMODULOS DE RANGO R DE DICHO HAZ, SUBMODULOS DE RANGO N-R DE SU DUAL Y SUBMODULOS INVERSIBLES DE SU R-ESIMA POTENCIA EXTERIOR SE APLICAN ESTOS RESULTADOS AL HAZ DE FORMAS SOBRE UNA VARIEDAD ALGEBRAICA NO SINGULAR PARA, ANADIENDO LA CONDICION DE INTEGRABILIDAD, OBTENER EL CONCEPTO DE FOLIACION SINGULAR, A PARTIR DE AQUI SE DEFINEN Y ESTUDIAN LOS CONCEPTOS DE SEPARATRIZ E INTEGRAL PRIMERA DE UNA FOLIACION SINGULAR SOBRE EL PLANO PROYECTIVO COMPLEJO PUEDE TRANSFORMARSE, MEDIANTE LA COMPOSICION DE UN NUMERO FINITO DE TRANSFORMACIONES DE CREMONA, EN OTRA FOLIACION (TAMBIEN DEFINIDA SOBRE EL PLANO PROYECTIVO COMPLEJO) CUYAS SINGULARIDADES SON O BIEN SIMPLES (EN EL SENTIDO DE SEINDENBERG) O BIEN ACEPTABLES (CONTRACCION DE UNA CURVA LISA CUYAS TANGENCIAS CON LAS SEPARATRICES DE LA FOLIACION NO SON MULTIPLES).
Transfer learning for brain decoding using deep architectures

Is there a general representation of the information content of human brain, which can be extracted from the functional magnetic resonance imaging (fMRI) data? Is it possible to learn this representation automatically from big data sets by unsupervised learning methods? Is it possible to transfer this representation to learn and decode a set of cognitive states in other fMRI data sets? This study addresses partial answers to the above questions by using transfer learning in deep architectures. First, a hierarchical representation for fMRI data is learned from a large data set in Human Connectome Project (HCP) by a 3-layered stacked denoising autoencoder (SDAE). Then, the learned representations are used to train and recognize the cognitive states recorded by a relatively small data set of one-back repetition detection experiment. Results show that, it is possible to learn a general representation and transfer the learned representation of an fMRI data set to another dataset for brain decoding problem. The learned representation has a better discriminative power compared to the Pearson correlation features. Results also show us that deep neural networks transfer representations better than factor models commonly used in pattern recognition and neuroscience literature.
Vocal tract length normalization using rapid maximum-likelihood estimation for speech recognition

Speaker normalization techniques for correcting differences in the vocal tract lengths of different speakers, referred to as vocal tract length normalization, in a large vocabulary voice recognition system using a hidden Markov model (HMM), have been proposed in recent years. In this paper, a scheme for approximating especially small changes in the vocal tract length by linear mapping using a vocal tract length parameter in cepstrum space and maximum-likelihood estimation of this parameter from vocalization is proposed. The proposed method can estimate a more optimal parameter for a speaker with a small amount of computation than in past schemes using multiple vocal tract length parameters in advance. In evaluation tests of the recognition of 5000 single Japanese words, the proposed scheme decreased errors by 7.1% alone and 14.6% in combination with cepstrum mean normalization (CMN). © 2002 Wiley Periodicals, Inc. Syst Comp Jpn, 33(5): 30–40, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.1125
Prediction of Side Chain Orientations in Proteins by Statistical Machine Learning Methods

Abstract We develop ways to predict the side chain orientations of residues within a protein structure by using several different statistical machine learning methods. Here side chain orientation of a given residue i is measured by an angle Ωi between the vector pointing from the center of the protein structure to the Cα i atom and the vector pointing from the Cα i atom to the center of its side chain atoms. To predict the Ωi angles, we construct statistical models by using several different methods such as general linear regression, a regression tree and bagging, a neural network, and a support vector machine. The root mean square errors for the different models range only from 36.67 to 37.60 degrees and the correlation coefficients are all between 30% and 34%. The performances of different models in the test set are, thus, quite similar, and show the relative predictive power of these models to be significant in comparison with random side chain orientations.
Effect of Real-Time Electricity Pricing on Ancillary Service Requirements

The objective of this work is to analyze the effect of real time electricity price (RTP) on the amount of ancillary services required for load balancing in presence of responsive users, information asymmetry and forecast errors in demand and renewable energy sources (RES) generation. We consider a RTP that is determined by the forecasted generation and ramping cost. A community choice aggregator manages the load of all the consumers by setting the price. The consumer's objective is to minimize their overall cost of consumption. Ancillary services are called upon to balance the load in real time. With zero RES in the power network and a high degree of load flexibility, the proposed RTP flattens and the volatility in demand vanishes. However, in presence of RES the volatility in price and demand is reduced up to an extent and ancillary services are required for load balancing. The amount of ancillary services required increases with forecast errors. We also propose a real time algorithm that approximates the optimal consumer behavior under the complete information setting. Extensive numerical simulations are provided using real data from Pecan Street and Elia Belgium.
Gene expression profiles and molecular markers to predict recurrence of Dukes' B colon cancer.

PURPOSE The 5-year survival rate of patients with Dukes' B colon cancer is approximately 75%. Identification of the patients at high risk of recurrence in this group would allow better staging and more informed use of adjuvant chemotherapy. In this study, we used DNA chip technology to systematically identify new prognostic markers for tumor relapse in Dukes' B patients. PATIENTS AND METHODS Using Affymetrix U133a GeneChip containing approximately 22,000 transcripts (Affymetrix, Santa Clara, CA), RNA samples from 74 patients with Dukes' B colon cancer were analyzed. Thirty-one patients developed tumor relapse in less than 3 years, whereas 43 patients remained disease-free for more than 3 years after surgery. Two supervised class prediction approaches were used to identify gene markers that can best discriminate between patients who would experience relapse and patients who would remain disease-free. A multivariate Cox model was built to predict recurrence. RESULTS Gene expression profiling identified a 23-gene signature that predicts recurrence in Dukes' B patients. This signature was validated in 36 independent patients. The overall performance accuracy was 78%. Thirteen of 18 relapse patients and 15 of 18 disease-free patients were predicted correctly, giving an odds ratio of 13 (95% CI, 2.6 to 65; P =.003). The log-rank test indicated a significant difference in disease-free time between the predicted relapse and disease-free patients (P =.0001). CONCLUSION The clinical value of these markers is that the patients at a high predicted risk of relapse (13-fold risk) could be upstaged to receive adjuvant therapy, similar to Dukes' C patients. Our data highlight the feasibility of a prognostic assay that could focus more intensive treatment for localized colon cancer.
Indonesian Marine Tourism: Developing a Favorable Tourism Destination to Attract International Sailing Boats

The objective of this paper is to identify the Strengths, Weaknesses, Opportunities, and Threats (SWOT) of Sailing Yacht tourism based on empirical evidence, mainly on demand aspects. The results will be very useful for decision-makers to design, launch and control marketing strategies and policies including promotional aspects to increase the awareness of the yacht sailors from various parts of the world, arouse their intention to come, increase spending and length of stay in Sabang as a free trade zone in west part of Indonesia. Data collection was conducted qualitatively by using the Focus Group Discussion (FGD) technique conducted in four sessions. Each session involves ten sailors who serve as respondents. The data were then analyzed using both score and weight associated with IFAS and EFAS aspects. The output is mapped in Cartesian graphs. The main finding of this study is that the strategy that must be implemented by Sabang is an Aggressive strategy, which uses the Strength to seize the profitable Opportunities. This is in line with the combined strategy that recommends Strength Opportunity (SO) as a priority strategy because it has the highest value of 16.92. In sequence, the next strategy is Weakness Opportunities (WO) that is meant to fix the Weakness in other to be able to grab the profitable Opportunities so that untapped opportunities can be utilized for the benefit of the sailors and tour operators. Then, ST and WT strategies will be implemented to complete all 4 strategies recommended. With the implementation of these four strategies based on the priority scale, it is expected to maximize the utilization of limited resources, but also at the same time maximize the efforts made to achieve the goal of increasing the number of sailor visits to Sabang, Indonesia and increasing their length of stay.
Idiotypic analysis of the response of C57BL/6 mice to the (4‐hydroxy‐3‐nitrophenyl)acetyl group

Strain C57BL/6 mice produce a highly restricted primary response to the (4‐hydroxy‐3‐nitrophenyl)acetyl (NP) group. This response is composed of molecules having μ or γ1 heavy chains and light chains of the λ type. A guinea pig anti‐idiotype was raised to the purified C57BL/6 primary anti‐NP immunoglobulin. After suitable absorption, this anti‐idiotype was shown to detect markers present on the primary anti‐NP immunoglobulin only of those strains which express the Ig‐lb allotype. Breeding experiments demonstrated that the marker segregated with the heavy chain linkage group.
Trust‐annotated ontology integration using social modelling *

Abstract: As ontologies become more prevalent for information management the need to manage the ontologies increases. Multiple organizations, within a domain, often combine to work on specific projects. When separate organizations come together to communicate, an alignment of terminology and semantics is required. Ontology creation is often privatized for these individual organizations to represent their view of the domain. This creates problems with alignment and integration, making it necessary to consider how much each ontology should influence the current decision to be made. To assist with determining influence a trust‐based approach on authors and their ontologies provides a mechanism for ranking reasoning results. A representation of authors and the individual resources they provide for the merged ontology becomes necessary. The authors are then weighted by trust and trust for the resources they provide the ontology is calculated. This is then used to assist the integration process allowing for an evolutionary trust model to calculate the level of credibility of resources. Once the integration is complete semantic agreement between ontologies allows for the revision of the authors' trust.
Effect of Human Capital on Productivity and Efficiency in the Banking Sector: An Exploratory Study of Sri Lanka and New Zealand

The performance of world class manufacturing companies is not only based on equipment, material, and processes but also human capital. Thus, this research contributes and extends the existing knowledge on human capital to provide a comprehensive understanding by exploring following questions: “How do human capital effect on productivity and efficiency? ” and ”How do human capital and its role on productivity and efficiency in the banking sector in Sri Lanka differ from that in New Zealand? ”. This research employed a qualitative case study as a research approach. Data is collected, via conducting in-depth interviews, and gathering information from available secondary sources from 10 banks in two nations, Sri Lanka and New Zealand. Data analysis is done through content analysis which resulted in a comprehensive understanding of the relationship between HC and the productivity and efficiency in the banking sector in a developing country, Sri Lanka and a developed country, New Zealand. This study revealed that HC has the potential to enhance overall productivity and efficiency in thebanking sector in both contexts. Comparative analysis suggests that although some differences existed, views on the importance of having HC to enhance productivity and efficiency in these two countries were consistent.
Energy optimization for full-duplex self-backhauled HetNet with non-orthogonal multiple access

Small cell densification and advanced multi-user access schemes are promising approaches to dramatically improve 5G system performance. Towards efficient spectrum usage in ultra-dense heterogeneous networks, spectrum reuse between backhauling and access links combined with full duplex is applied. This forms a full-duplex self-backhauled heterogeneous network (FS-HetNet). Considering co-channel interference caused by frequency reuse, and residual self interference due to imperfect interference cancellation in full duplex, interference management becomes a major issue in boosting network performance. In this paper, motivated by the emerging non-orthogonal multiple access (NOMA) for 5G, we consider a NOMA-based scheme to mitigate co-channel interference and achieve efficient spectrum utilization for FS-HetNet. We address an energy-saving problem for the considered network, aiming to satisfy all users' data demand within a limited transmit duration by consuming minimum energy. In addition to the energy consumption in transmission, the consumed decoding energy due to signal processing in successive interference cancellation is also taken into account. We propose an energy-efficient and delay-constrained scheduling algorithm to jointly optimize transmit power, user clustering, and transmission duration. Numerical results demonstrate that the proposed approach outperforms previous schemes.
GENDER DIFFERENCES OF MANAGING BANKS´ CREDIT PORTFOLIO

The article aimed to demonstrate whether the quality of decision-making on lending to clients in the small and medium-sized business sector is influenced by the gender of the approvers or their direct motivation caused by share on business results. The motivation for this research were the studies conducted after the last global financial crisis, mostly in the US and Europe, to a lesser extent in the Czech Republic. Their authors tend to conclude that women show better credit risk management than men and that direct managers' engagement in business results and profits generates a higher susceptibility to risky, erroneous decisions. The research was carried out on one of the major banks operating in the Czech Republic, on a nationwide sample of workers with the loan approval authority in the segment of small and medium-sized firms. The decision of the approvers was, based on a random selection of about 1/3 of all their decisions, subject to control over three consecutive years. The obtained data were analysed by ANOVA, which did not prove the dependence of the decision quality on the gender or the direct motivation of the approver on business results. The research and its results have opened up scope for further research on the issue with a focus on a qualitative analysis of the nature and severity of the mistakes in terms of gender, job position, the level of authorization power and, last but not least, the unequal representation of women in the management of domestic banks.
Crowdsourcing in a Public Organization: Transformation and Culture

Employees increasingly want to participate in the decision-making processes of their organization. Approaches that facilitate organizational participation, such as internal crowdsourcing platforms, can achieve this. However, although organizations of various backgrounds should be able to reap benefits from such systems, in practice, implementation might fail due to an organizational culture built on hierarchical structures, low experience with employee participation and fixed processes. Taking a design science approach, we explore this relation in a five-month case study of a transformational process at a public organization. We design, implement and evaluate an information system for internal crowdsourcing. Based on the results from user-generated content analysis of the proposals and comments, survey data and several in-depth interviews, we observe an IT culture conflict that significantly affects system adoption and use. Our findings contribute to the discussion on theoretical and practical implications for design and implementation of information systems in organizational contexts.
Innate immunity in heart transplantation

Purpose of reviewCardiac transplantation is the treatment of choice for end-stage heart failure, but its efficacy is limited by the development of cardiac allograft vasculopathy (CAV). Although the adaptive immune system is efficiently suppressed by conventional drugs, the innate immune system is largely unaffected. The innate response may contribute both to stimulation of the adaptive response and to the future development of CAV. Recent findingsStimulation of Toll-like receptors by endogenous ligands released in response to ischemia/reperfusion causes an inflammatory milieu favorable to graft rejection and unfavorable to tolerance. New evidence suggests that natural killer cells have previously unknown memory-like features and are capable of graft rejection. Their role in rejecting the cardiac allograft has previously been underestimated. Complement deposition may also contribute to acute cellular rejection and CAV. SummaryThe innate immune system is an important but neglected component of allograft rejection. Drugs that target Toll-like receptors, natural killer cells and complement may play an important role in preventing CAV and achieving tolerance to cardiac allografts.