Miracle-dz/UniFAR-FTUs huggingface dataset:
Krill Products: An Overview of Animal Studies

Many animal studies have been performed with krill oil (KO) and this review aims to summarize their findings and give insight into the mechanism of action of KO. Animal models that have been used in studies with KO include obesity, depression, myocardial infarction, chronic low-grade and ulcerative inflammation and are described in detail. Moreover, studies with KO in the form of krill powder (KP) and krill protein concentrate (KPC) as a mix of lipids and proteins are mentioned and compared to the effects of KO. In addition, differences in tissue uptake of the long-chain omega-3 polyunsaturated fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), when delivered in either phospholipid or triglyceride form, are addressed and the differential impact the delivery form has on gene expression profiles is explained. In our outlook, we try to highlight the potential of KO and KP supplementation in clinical settings and discuss health segments that have a high potential of showing krill product specific health benefits and warrant further clinical investigations.
Comparison of Intradialytic Parenteral Nutrition with Glucose or Amino Acid Mixtures in Maintenance Hemodialysis Patients

Many long-term maintenance hemodialysis patients have symptoms of protein-energy wasting caused by malnutrition. Each session of hemodialysis removes about 10 to 12 g of amino acids and 200 to 480 kcal of energy. Patients receiving hemodialysis for chronic kidney disease may be undernourished for energy, protein consumption, or both. Non-diabetic hemodialysis patients were randomized to three treatment groups: oral supplementation, oral supplementation plus high-concentration glucose solution (250 mL containing 50% glucose) and these two interventions plus 8.5% amino acids solution. The post-treatment energy status of the glucose group was significantly higher than its baseline level, whereas the control group’s status was significantly lower. The glucose group had significantly higher concentrations of asparagine, glutamine, glycine, alanine, and lysine after treatment. All treatment groups had significantly increased hemoglobin levels but significantly decreased transferrin levels after treatment compared to baseline. After treatment, the amino acid group had significantly higher albumin level compared to the glucose group (p = 0.001) and significantly higher prealbumin level compared to the control group (p = 0.017). In conclusion, long-term intervention with high-concentration glucose solution at each hemodialysis session is a simple and cheap method that replenished energy stores lost during hemodialysis of non-diabetic patients.
MINING MULTIDIMENSIONAL FUZZY ASSOCIATION RULES FROM A DATABASE OF MEDICAL RECORD PATIENTS

Mining association rules is one of the important tasks in the process of data mining application. In general, the input as used in the process of generating rules is taken from a certain data table by which all the corresponding values of every domain data have correlations one to each others as given in the table. A problem arises when we need to generate the rules expressing the relationship between two or more domains that belong to several different tables in a normalized database. To overcome the problem, before generating rules it is necessary to join the participant tables into a general table by a process called Denormalization Process. This paper shows a process of generating Multidimensional Fuzzy Association Rules mining from a normalized database of medical record patients. The process consists of two sub-processes, namely sub-process of join tables (Denormalization Process) and sub-process of generating fuzzy rules. In general, the process of generating the fuzzy rules has been discussed in our previous papers [1, 2, 3, 4]. In addition to the process of generating fuzzy rules, this paper proposes a correlation measure of the rules as an additional consideration for evaluating interestingness of provided rules.
Human Genetic Disorders and Knockout Mice Deficient in Glycosaminoglycan

Glycosaminoglycans (GAGs) are constructed through the stepwise addition of respective monosaccharides by various glycosyltransferases and maturated by epimerases and sulfotransferases. The structural diversity of GAG polysaccharides, including their sulfation patterns and sequential arrangements, is essential for a wide range of biological activities such as cell signaling, cell proliferation, tissue morphogenesis, and interactions with various growth factors. Studies using knockout mice of enzymes responsible for the biosynthesis of the GAG side chains of proteoglycans have revealed their physiological functions. Furthermore, mutations in the human genes encoding glycosyltransferases, sulfotransferases, and related enzymes responsible for the biosynthesis of GAGs cause a number of genetic disorders including chondrodysplasia, spondyloepiphyseal dysplasia, and Ehlers-Danlos syndromes. This review focused on the increasing number of glycobiological studies on knockout mice and genetic diseases caused by disturbances in the biosynthetic enzymes for GAGs.
Flexible regression models over river networks

Many statistical models are available for spatial data but the vast majority of these assume that spatial separation can be measured by Euclidean distance. Data which are collected over river networks constitute a notable and commonly occurring exception, where distance must be measured along complex paths and, in addition, account must be taken of the relative flows of water into and out of confluences. Suitable models for this type of data have been constructed based on covariance functions. The aim of the paper is to place the focus on underlying spatial trends by adopting a regression formulation and using methods which allow smooth but flexible patterns. Specifically, kernel methods and penalized splines are investigated, with the latter proving more suitable from both computational and modelling perspectives. In addition to their use in a purely spatial setting, penalized splines also offer a convenient route to the construction of spatiotemporal models, where data are available over time as well as over space. Models which include main effects and spatiotemporal interactions, as well as seasonal terms and interactions, are constructed for data on nitrate pollution in the River Tweed. The results give valuable insight into the changes in water quality in both space and time.
Epidemiology of invasive cutaneous melanoma

Data are presented on the current incidence of melanoma with recent and predicted future trends illustrating a likely continuing increase in incidence. Risk factors for developing melanoma are discussed, including current known melanoma susceptibility genes. Phenotypic markers of high-risk subjects include high counts of benign melanocytic naevi. Other risk factors considered include exposure to natural and artificial ultraviolet radiation, the effect of female sex hormones, socioeconomic status, occupation, exposure to pesticides and ingestion of therapeutic drugs including immunosuppressives and non-steroidal anti-inflammatory drugs. Aids to earlier diagnosis are considered, including public education, screening and use of equipment such as the dermatoscope. Finally, the current pattern of survival and mortality is described.
Numerical Optimization of Silent Airfoil Sections

Within the work of the EU-funded SIROCCO project new airfoils for the tip region of two reference wind turbines are being designed with the objective to reduce the trailing-edge noise while maintaining the performance. The present paper focuses on the description of the optimization tools along with the aerodynamic and aeroacoustic prediction methods used. Comparisons with detailed boundary-layer experiments and aeroacoustic measurements conducted in the Laminar Wind-Tunnel of the IAG have shown that the accurate prediction of boundarylayer history and anisotropy effects have a decisive impact on the consistency of the noise prediction. The aerodynamic analysis method was extended to better account for these aspects. Extensive validations demonstrated the enhancements.
Human gesture recognition using orientation segmentation feature on random rorest

In the field of gesture recognition, one of the major challenges lies in that different user may sign different style of gesture. Traditional exemplar-based methods are vulnerable to gesture scaling and hand location translating. To overcome such disadvantage, we propose an efficient and inexpensive solution for classifying hand gestures by defining an invariant feature and applying it on random forest. One of the prominent characteristics of gesture is the underlying sequence structure, which can be greatly distinguished from other gestures. Hence, direction of gesture sequence segments has been established as simple comparison features for training random forest classifier, and then predicting gestures at sign piece level. The property of this feature determines that our recognition method can invariant to gesture scaling and hand location translating. It is free to act gesture at any angular field of view and not subject to different acting style of signer. The results show that the performance of proposed method outweighs other state-of-art methods for gesture recognition.
The Role of Reward in Dynamic Decision Making

The present study investigates two aspects of decision making that have yet to be explored within a dynamic environment, (1) comparing the accuracy of cue-outcome knowledge under conditions in which knowledge acquisition is either through Prediction or Choice, and (2) examining the effects of reward on both Prediction and Choice. In the present study participants either learnt about the cue-outcome relations in the environment by choosing cue values in order to maintain an outcome to criterion (Choice-based decision making), or learnt to predict the outcome from seeing changes to the cue values (Prediction-based decision making). During training participants received outcome feedback and one of four types of reward manipulations: Positive Reward, Negative Reward, Both Positive + Negative Reward, No Reward. After training both groups of learners were tested on prediction and choice-based tasks. In the main, the findings revealed that cue-outcome knowledge was more accurate when knowledge acquisition was Choice-based rather than Prediction-based. During learning Negative Reward adversely affected Choice-based decision making while Positive Reward adversely affected predictive-based decision making. During the test phase only performance on tests of choice was adversely affected by having received Positive Reward or Negative Reward during training. This article proposes that the adverse effects of reward may reflect the additional demands placed on processing rewards which compete for cognitive resources required to perform the main goal of the task. This in turn implies that, rather than facilitate decision making, the presentation of rewards can interfere with Choice-based and Prediction-based decisions.
Measuring user experience of a potential shipment tracking application

The existence of an application for monitoring the current position of product shipment can build user trust for the agency. Here, we have an application which simulates the status of travelling position. We assume that this application can be applied in shipment tracking problem. User experience describes the significance of the application on the end-user. Additional questionnaire items were given to participants for examining the merit of current application with shipment position monitoring. User Experience Questionnaire (UEQ) is employed to support a quick assessment of user experience for the product. Cronbach's Alpha value was measured to see the consistency of items of the scales and the relevancy of questionnaire items to the context.
Sensory and behavioral properties of neurons in posterior parietal cortex of the awake, trained monkey.

: Neurons in posterior parietal cortex of the awake, trained monkey respond to passive visual and/or somatosensory stimuli. In general, the receptive fields of these cells are large and nonspecific. When these neurons are studied during visually guided hand movements and eye movements, most of their activity can be accounted for by passive sensory stimulation. However, for some visual cells, the response to a stimulus is enhanced when it is to be the target for a saccadic eye movement. This enhancement is selective for eye movements into the visual receptive field since it does not occur with eye movements to other parts of the visual field. Cells that discharge in association with a visual fixation task have foveal receptive fields and respond to the spots of light used as fixation targets. Cells discharging selectively in association with different directions of tracking eye movements have directionally selective responses to moving visual stimuli. Every cell in our sample discharging in association with movement could be driven by passive sensory stimuli. We conclude that the activity of neurons in posterior parietal cortex is dependent on and indicative of external stimuli but not predictive of movement.
Population Synthesis via k-Nearest Neighbor Crossover Kernel

The recent development of multi-agent simulations brings about a need for population synthesis. It is a task of reconstructing the entire population from a sampling survey of limited size (1% or so), supplying the initial conditions from which simulations begin. This paper presents a new kernel density estimator for this task. Our method is an analogue of the classical Breiman-Meisel-Purcell estimator, but employs novel techniques that harness the huge degree of freedom which is required to model high-dimensional nonlinearly correlated datasets: the crossover kernel, the k-nearest neighbor restriction of the kernel construction set and the bagging of kernels. The performance as a statistical estimator is examined through real and synthetic datasets. We provide an "optimization-free" parameter selection rule for our method, a theory of how our method works and a computational cost analysis. To demonstrate the usefulness as a population synthesizer, our method is applied to a household synthesis task for an urban micro-simulator.
Human papillomavirus testing as an optional screening tool in low-resource settings of Latin America: experience from the Latin American Screening study

Hybrid capture II (HC II) test for oncogenic human papillomaviruses (HPV) was carried out in a cohort of 4284 women at their first clinical visit. Overall prevalence of HPV was 17.1%, decreasing with age from 33.9% among women below 20 years to only 11.0% among those older than 41 years. HPV prevalence was significantly higher among current smokers (odds ratio [OR] = 1.31; 95% CI 1.1–1.6), in women with two or more lifetime sexual partners (OR = 1.9; 95% CI 1.6–2.4), and those women with two or more sexual partners during the past 12 months prior to examination (OR = 1.6; 95% CI 1.2–2.2). HPV detection increased in parallel with increasing cytologic abnormality, being highest in women with high-grade squamous intraepithelial lesion (P = 0.001). Specificity of the HPV test in detecting histologically confirmed cervical disease was 85% (95% CI 83.9–86.1). Sensitivity of the HPV test in detecting histologic abnormalities increased in parallel with disease severity, ranging from 51.5% for cervical intraepithelial neoplasia (CIN) 1 to 96.5% for CIN 3 and 100.0% for cancer, with respective decline of positive predictive value. These data suggest that HPV testing with HC II assay might be a viable screening tool among this population with relatively high prevalence of cervical disease.
Serum Uric Acid Is Positively Associated with Handgrip Strength among Japanese Community-Dwelling Elderly Women

Serum uric acid (UA) has strong anti-oxidant properties. Muscle strength and mass decrease with age, and recently, this decrease has been defined as sarcopenia. Sarcopenia may be triggered by oxidative stress. We investigated whether serum UA is associated with handgrip strength (HGS), which is a useful indicator of sarcopenia, among Japanese community-dwelling elderly persons. The present study included 602 men aged 72 ± 7 years and 847 women aged 71 ± 6 years from a rural village. We examined the cross-sectional relationship between serum UA and HGS. In both genders, HGS increased significantly with increased serum UA levels. A multiple linear regression analysis using HGS as an objective variable and various confounding factors as explanatory variables showed that in men age, drinking status, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and estimated glomerular filtration ratio (eGFRCKDEPI) were independently and significantly associated with HGS, and in women, serum UA as well as age, body mass index, drinking status, diastolic blood pressure, and eGFRCKDEPI were independently and significantly associated with HGS. In women, age and multivariate-adjusted HGS were significantly higher in the Quartile-3 (4.8–5.4 mg/dL) and Quartile-4 groups (5.5–9.3 mg/dL) of serum UA than in the lower groups (0.7–4.7 mg/dL). These results suggest that serum UA may have a protective role in aging-associated decline in muscle strength in community-dwelling elderly women.
Smoothing human-robot speech interactions by using a blinking-light as subtle expression

Speech overlaps, undesired collisions of utterances between systems and users, harm smooth communication and degrade the usability of systems. We propose a method to enable smooth speech interactions between a user and a robot, which enables subtle expressions by the robot in the form of a blinking LED attached to its chest. In concrete terms, we show that, by blinking an LED from the end of the user's speech until the robot's speech, the number of undesirable repetitions, which are responsible for speech overlaps, decreases, while that of desirable repetitions increases. In experiments, participants played a last-and-first game with the robot. The experimental results suggest that the blinking-light can prevent speech overlaps between a user and a robot, speed up dialogues, and improve user's impressions.
Self-Leadership in Purposedriven Organizations: Analyzing Human Perception for More Integrated Decision- Making

Productive decision-making requires appropriate perception of the facts relevant to the decision. It may be necessary to perceive and integrate diverse and conflicting perspectives appearing inside and outside of the decision-maker. Therefore I scrutinize theoretical and empirical findings on individual human perception as a basis for decision-making and behavior. Special attention lies on the role of the unconscious (e.g. Bargh, 2006), dual-system approaches (e.g. Kahneman & Frederick, 2002), self-regulation (e.g. Muraven, Baumeister & Tice, 1999, Moffitt et al., 2011), and self-leadership (e.g. Manz, 2013). From this foundation I derive guiding self-leadership guidelines for more sustainable internal balancing and more comprehensive integration of external stimuli. Such self-leadership guidelines allow leaders and organizations to identify blind spots more easily and to improve the perception of the inside and the environment. In purpose-driven organizations with distributed authority, the power to decide is distributed among those employees who appear to be competent for the specific topic. Therefore especially within such organizations this self-leadership competency appears to be crucial for success.
Widely-linear beamforming/combining techniques for MIMO wireless systems

Joint design of beamforming and combining vectors for multiple-input multiple-output (MIMO) wireless systems is considered. The proposed approach employs widely-linear (WL) techniques, aimed at providing substantial performance gains over linear ones when the transmitted signal and/or the disturbance exhibit noncircularity features. Computer simulation results assess the claimed performance gains.
Global Metabolic Profiling of Infection by an Oncogenic Virus: KSHV Induces and Requires Lipogenesis for Survival of Latent Infection

Like cancer cells, virally infected cells have dramatically altered metabolic requirements. We analyzed global metabolic changes induced by latent infection with an oncogenic virus, Kaposi's Sarcoma-associated herpesvirus (KSHV). KSHV is the etiologic agent of Kaposi's Sarcoma (KS), the most common tumor of AIDS patients. Approximately one-third of the nearly 200 measured metabolites were altered following latent infection of endothelial cells by KSHV, including many metabolites of anabolic pathways common to most cancer cells. KSHV induced pathways that are commonly altered in cancer cells including glycolysis, the pentose phosphate pathway, amino acid production and fatty acid synthesis. Interestingly, over half of the detectable long chain fatty acids detected in our screen were significantly increased by latent KSHV infection. KSHV infection leads to the elevation of metabolites involved in the synthesis of fatty acids, not degradation from phospholipids, and leads to increased lipid droplet organelle formation in the infected cells. Fatty acid synthesis is required for the survival of latently infected endothelial cells, as inhibition of key enzymes in this pathway led to apoptosis of infected cells. Addition of palmitic acid to latently infected cells treated with a fatty acid synthesis inhibitor protected the cells from death indicating that the products of this pathway are essential. Our metabolomic analysis of KSHV-infected cells provides insight as to how oncogenic viruses can induce metabolic alterations common to cancer cells. Furthermore, this analysis raises the possibility that metabolic pathways may provide novel therapeutic targets for the inhibition of latent KSHV infection and ultimately KS tumors.
Synthesis, characterization and in vivo evaluation of cadmium telluride quantum dots toxicity in mice by toxicometabolomics approach

Abstract Quantum dots (QDs) have widespread application in many fields such as medicine and electronics. The need for understanding the potentially harmful side effects of these materials becomes clear. In this study, the toxicity of cadmium telluride quantum dots (CdTe-QDs) and bulk Cd2+ has been investigated and compared by applying metabolomics methods. The datasets were 1H-NMR data from mice plasma which had been taken from four groups of mice in different time intervals. Then, the data were analyzed by applying chemometrics methods and the metabolites were found from Human Metabolome Database (HMDB). The results showed the significant change in the level of some metabolites especially estrogenic steroids in different groups with different amounts of received Cd. The findings also indicated that steroid hormone biosynthesis, lysine biosynthesis and taurine and hypotaurine metabolism are the most affected pathways by CdTe-QDs especially in estrogenic steroids. The over-representation analysis indicated that endoplasmic reticulum, gonads, and hepatocytes are most affected. Since the pattern of metabolite alteration of CdTe-QDs with equivalent Cd2+ was similar to those of CdCl2, it was postulated that beside Cd2+ effects, the toxicity of CdTe-QDs is associated with other factors.
Gecko: A Contention-Oblivious Design for Cloud Storage

Disk contention is a fact of life in modern data centers, with multiple applications sharing the storage resources of a single physical machine. Log-structured storage designs are ideally suited for such high-contention settings, but historically have suffered from performance problems due to cleaning overheads. In this paper, we introduce Gecko, a novel design for storage arrays where a single log structure is distributed across a chain of drives, physically separating the tail of the log (where writes occur) from its body. This design provides the benefits of logging - fast, sequential writes for any number of contending applications - while eliminating the disruptive effect of log cleaning activity on application I/O.