Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating glomerular filtration rate in black South Africans by use of the modification of diet in renal disease and Cockcroft-Gault equations.

BACKGROUND The 4-variable Modification of Diet in Renal Disease (4-v MDRD) and Cockcroft-Gault (CG) equations are commonly used for estimating glomerular filtration rate (GFR); however, neither of these equations has been validated in an indigenous African population. The aim of this study was to evaluate the performance of the 4-v MDRD and CG equations for estimating GFR in black South Africans against measured GFR and to assess the appropriateness for the local population of the ethnicity factor established for African Americans in the 4-v MDRD equation. METHODS We enrolled 100 patients in the study. The plasma clearance of chromium-51-EDTA ((51)Cr-EDTA) was used to measure GFR, and serum creatinine was measured using an isotope dilution mass spectrometry (IDMS) traceable assay. We estimated GFR using both the reexpressed 4-v MDRD and CG equations and compared it to measured GFR using 4 modalities: correlation coefficient, weighted Deming regression analysis, percentage bias, and proportion of estimated GFR within 30% of measured GFR (P(30)). RESULTS The Spearman correlation coefficient between measured and estimated GFR for both equations was similar (4-v MDRD R(2) = 0.80 and CG R(2) = 0.79). Using the 4-v MDRD equation with the ethnicity factor of 1.212 as established for African Americans resulted in a median positive bias of 13.1 (95% CI 5.5 to 18.3) mL/min/1.73 m(2). Without the ethnicity factor, median bias was 1.9 (95% CI -0.8 to 4.5) mL/min/1.73 m(2). CONCLUSIONS The 4-v MDRD equation, without the ethnicity factor of 1.212, can be used for estimating GFR in black South Africans.
A universally manipulable body model: Application of the MMC principle to a dual quaternion representation

Internal models are assumed to be a prerequisite for getting cognitive. In this article, I introduce a neural network approach for a model representing the kinematics of a complex manipulator which at the same time can be used for solving inverse and forward kinematic function. The Mean of Multiple Computation principle applied to a dual quaternion representation of transformations describing the manipulator is extendable to integrate into the model additional sensory information or information concerning the environment. It will be discussed how the body model presented may serve functions related to specific behaviours like targeted movements. But the model is suited to be applied in a more universal way. It can be used for planning ahead in a form of mental simulation for predictive purposes. The principle proposed can be applied to arbitrarily complex geometrical structures.
Holmes: A data theft forensic framework

This paper presents Holmes, a forensic framework for postmortem investigation of data theft incidents in enterprise networks. Holmes pro-actively collects potential evidence from hosts and the network for correlation analysis at a central location. In order to optimize the storage requirements for the collected data, Holmes relies on compact network and host data structures. We evaluate the theoretical storage requirements of Holmes in average networks and quantify the improvements compared to raw data collection alternatives. Finally, we present the application of Holmes to two realistic data theft investigation scenarios and discuss how combining network and host data can improve the efficiency and reliability of these investigations.
Contention Based Multichannel MAC Protocol for Distributed Cognitive Radio Networks

Design of an efficient medium access control protocol is critical for proper functioning of a distributed cognitive radio network and better utilization of the channels not being used by primary users. In this paper, we design a contention based distributed medium access control (MAC) protocol for the secondary users' channel access. The proposed MAC protocol allows collision-free access to the available data channels and eventually their utilization by secondary users, with spectrum sensing part being handled by exclusive sensing nodes. We further introduce the provision of reservation of free channels by secondaries for extended periods to increase utilization without causing harmful interference to primaries. We demonstrate how such extended access to resources can be tuned to provide differential quality of service to the secondary users. The effectiveness of the protocol is evaluated by performing analysis and simulation. We use blocking probability, secondary usage of a secondary user and performance degradation caused to primary incumbents as performance metrics. We obtain the conditions for such extended access and try to gauge the resulting increase in utilization. Under optimal conditions, the proposed scheme enables the secondary network to utilize all available channels. The proposed scheme is shown to outperform the most sophisticated existing MAC schemes for distributed secondary networks.
Reading detection based on electroencephalogram processing

This paper describes a study regarding the detection of silent visual reading and non reading mental activities through electroencephalogram (EEG) processing. Our work is in the context of human computer interaction research field, and we pretend to integrate EEG signals in applications to assist and analyze reading tasks. The need of users to be constantly and tightly coupled with the applications is being highly stimulated by the design of universally-accessible interactive system, where the use of biomedical signals has become an emerging area. The work focuses on building reliable capture and preprocessing procedures, extracting relevant features and testing simple learning algorithms. The detection process uses left hemisphere EEG signals, which is referred to as being the relevant brain area for this type of tasks. The signals were processed to extract the power spectrum density of delta, theta and alpha rhythms, known frequencies of this type of signals. We also present two real time demonstration applications,
Transcranial Direct Current Stimulation Reduces Negative Affect but Not Cigarette Craving in Overnight Abstinent Smokers

Transcranial direct current stimulation (tDCS) can enhance cognitive control functions including attention and top-down regulation over negative affect and substance craving in both healthy and clinical populations, including early abstinent (∼1.5 h) smokers. The aim of this study was to assess whether tDCS modulates negative affect, cigarette craving, and attention of overnight abstinent tobacco dependent smokers. In this study, 24 smokers received a real and a sham session of tDCS after overnight abstinence from smoking on two different days. We applied anode to the left dorsolateral prefrontal cortex and cathode to the right supra-orbital area for 20 min with a current of 2.0 mA. We used self-report questionnaires Profile of Mood States (POMS) to assess negative affect and Urge to Smoke (UTS) Scale to assess craving for cigarette smoking, and a computerized visual target identification task to assess attention immediately before and after each tDCS. Smokers reported significantly greater reductions in POMS scores of total mood disturbance and scores of tension–anxiety, depression–dejection, and confusion–bewilderment subscales after real relative to sham tDCS. Furthermore, this reduction in negative affect positively correlated with the level of nicotine dependence as assessed by Fagerström scale. However, reductions in cigarette craving after real vs. sham tDCS did not differ, nor were there differences in reaction time or hit rate change on the visual task. Smokers did not report significant side effects of tDCS. This study demonstrates the safety of tDCS and its promising effect in ameliorating negative affect in overnight abstinent smokers. Its efficacy in treating tobacco dependence deserves further investigation.
Netcoin: A Traceable P2P Electronic Cash System

This paper introduces a new P2P Electronic Cash system called Netcoin. The purpose of Net coin is to facilitate inexpensive peer-to-peer monetary transactions on the Web. Its salient features are that it is a traceable system with an efficient mechanism for verifying transactions. Net coins are reusable and can be easily passed from one user to another. The issuing of virtual currency and verification of transactions are performed by trusted mints, which act as the gateway between the fiat and virtual currency worlds. There is no need to maintain a public ledger, which would inhibit use on a global scale because of rapidly increasing memory and bandwidth requirements. The system is neither inflationary nor deflationary in nature and does not purport a new economic model. As a fiat-backed currency it should not suffer the volatility issues associated with Bit coin. In this paper the two most prominent electronic payment systems of the last forty years, namely Ecash and Bit coin, are examined. Net coin is then introduced in detail and is designed to address the shortcomings of these payment systems.
Occurrence and variation in the amount of Characean oospores in Estonian Late-glacial sediments : state of the art and prospectives

The Characeae oospores are frequently found in sediment samples during Quaternary palaecological studies. Counts of oospores of three Estonian Late-glacial (14000 – 11500 calibrated year before present, cal y BP) sediment cores are presented and discussed. The first postglacial findings of Characeae oospores in Estonia date back 13900 cal y BP confirming the early appearance of Characeae in postglacial water bodies. The oospores found in two southern localities belong to Chara spp. while only Nitella spp oospores are counted in lake situated hundred kilometers in North. In general the number of oospores is low, maximum 50 oospores per 100 cm and rises near to the Holocene boundary (11800 cal y BP). The significance and limits of oospore counts for palaeoecological studies are discussed. The studied territory is situated near to the Baltic Sea and has numerous inland lakes offering various possibilities for future applications of Characeae oospore analysis.
Lack of Cocaine Self-Administration in Mice Expressing a Cocaine-Insensitive Dopamine Transporter

Cocaine addiction is a worldwide public health problem for which there are no established treatments. The dopamine transporter (DAT) is suspected as the primary target mediating cocaine's abuse-related effects based on numerous pharmacological studies. However, in a previous study, DAT knockout mice were reported to self-administer cocaine, generating much debate regarding the importance of the DAT in cocaine's abuse-related effects. Here, we show that mice expressing a “knockin” of a cocaine-insensitive but functional DAT did not self-administer cocaine intravenously despite normal food-maintained responding and normal intravenous self-administration of amphetamine and a direct dopamine agonist. Our results have three implications. First, they imply a crucial role for high-affinity DAT binding of cocaine in mediating its reinforcing effects, reconciling mouse genetic engineering approaches with data from classic pharmacological studies. Second, they demonstrate the usefulness of knockin strategies that modify specific amino acid sequences within a protein. Third, they show that it is possible to alter the DAT protein sequence in such a way as to selectively target its interaction with cocaine, while sparing other behaviors dependent on DAT function. Thus, molecular engineering technology could advance the development of highly specialized compounds such as a dopamine-sparing “cocaine antagonist. ”
A re-usability approach to ontology construction

Knowledge Representation is largely based on ontologies in the Semantic Web. One of the major difficulties to construct ontology such that it meets the requirements of users is the high cost incurred and time consumed in building them. Gathering complete knowledge about the domain of disclosure is time consuming and may not guarantee expected results too. Therefore reuse of existing ontologies can offer a cost and time benefit alternative than building new ones from scratch. Hence, an approach is proposed to reuse the existing ontologies available on the web and online libraries to build new ontologies. This paper presents an approach to retrieve the required ontologies on basis of important terms of domain from online repositories using semantic web search engines, preprocess them as per our requirement and merge them to form the entire domain ontology.
A purely functional approach to packet processing

Today's rapidly evolving network ecosystem, characterized by increasing traffic volumes, service heterogeneity and mutating cyber-threats, calls for new approaches to packet processing to address key issues such as scalability, flexibility, programmability and fast deployment. To this aim, this paper explores a new direction to packet processing by pushing forward functional programming principles in the definition of a “software defined networking” paradigm. This result is achieved by introducing PFQ-Lang, an extensible functional language which can be used to process, analyze and forward packets captured on modern multi-queue NICs (for example, it allows to quickly develop the early stage of monitoring applications). An implementation of PFQ-Lang, embedded into high level programming languages as an eDSL (embedded Domain Specific Language) is also presented. The proposed approach allows an easy development by leveraging the intuitive functional composition and, at the same time, allows to exploit multi-queue NICs and multi-core architectures to process high-speed network traffic. Experimental results are provided to prove that the presented implementation reaches line rate performance on a 10Gb line card. To demonstrate the effectiveness and expressiveness of PFQ-Lang, the paper also presents a few use-cases ranging from forwarding, firewalling and monitoring of real traffic.
NIZE - a Near Field Communication interface enabling zero energy standby for everyday electronic devices

Standby power consumption of electric devices is a growing waste of energy. Between 5% and 14% of the residential electrical power consumption is caused by devices being in standby mode. Depending on the device type, more than 50% of standby power consumption could be saved by applying state-of-the-art power management techniques. By implementing a zero energy standby design and outsourcing power consuming user interfaces, even more electrical power can be saved. Here we present a novel Near Field Communication (NFC) interfacing method for everyday electronic devices. By implementing this interface, the target device can be shut down during idle times. Thus, standby power consumption is eliminated completely. If user interaction is requested, NFC provides the electrical energy to switch on the target device's power supply and to start the device. Furthermore, any control, status, and maintenance information can be transmitted over NFC. By outsourcing high power dissipating and unoptimized user interfaces (touch screens, WiFi, etc.) to the power optimized NFC reader, further energy savings are possible also during running state. This paper demonstrates the implementation and integration of this novel interfacing technique into common consumer electronics. Two implementation approaches are presented. A simple, energy harvesting-based approach illustrates the basic working principle. The second, more sophisticated approach, enables also authentication, encrypted data transfer, user interface outsourcing, configuration and control tasks, etc. A proof of concept is demonstrated by means of an access control terminal.
De Bruijn Sequences for Fixed-Weight Binary Strings

De Bruijn sequences are circular strings of length $2^n$ whose length n substrings are the binary strings of length n. Our focus is on creating circular strings of length $\binom{n}{w}$ for the binary strings of length n with weight (number of 1s) equal to w. In this case, each fixed-weight string can be encoded by its first $n{-}1$ bits since the final bit is redundant. For this reason, we construct circular strings of length $\binom{n-1}{w}+\binom{n-1}{w-1}$ whose length $n{-}1$ substrings are the binary strings of length $n{-}1$ with weight w or $w{-}1$. Our construction is reminiscent of the construction for the lexicographically least de Bruijn sequence, except the underlying algorithm is applied to cool-lex order instead of lexicographic order. The construction can be efficiently implemented so that successive blocks of n bits are generated in constant amortized time while using $O(n \log n)$-space. This article's results were also used to create de Bruijn sequences for binary strings of length n wi.
Individual differences in psychophysiological reactivity in adults with childhood abuse

Little is known about the neurobiological correlates of stress-related disorders. In particular almost nothing is known about biological correlates of specific personality disorders that have been linked to stress. We measured heart rate and blood pressure reactivity in response to personalized traumatic scripts together with subjective psychological ratings in four women with a history of childhood abuse with no disorder, Posttraumatic Stress Disorder, Borderline Personality Disorder, and Histrionic Personality Disorder. Psychophysiology as well as subjective ratings differed markedly between the four women, with elevated reactions found in PTSD and histrionic personality, and extreme decline in physiological reactivity associated with a dissociative response in the borderline patient. It is concluded that reactivity to traumatic reminders can be correlated with the existence of different stress-related diagnoses. Personality characteristics seem to have an influence on psychophysiological reactivity in patients with stress-related psychiatric disorders. Copyright © 2002 John Wiley & Sons, Ltd.
A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference

Modeling continuous-time physiological processes that manifest a patient's evolving clinical states is a key step in approaching many problems in healthcare. In this paper, we develop the Hidden Absorbing Semi-Markov Model (HASMM): a versatile probabilistic model that is capable of capturing the modern electronic health record (EHR) data. Unlike existing models, the HASMM accommodates irregularly sampled, temporally correlated, and informatively censored physiological data, and can describe non-stationary clinical state transitions. Learning the HASMM parameters from the EHR data is achieved via a novel forward-filtering backward-sampling Monte-Carlo EM algorithm that exploits the knowledge of the end-point clinical outcomes (informative censoring) in the EHR data, and implements the E-step by sequentially sampling the patients' clinical states in the reverse-time direction while conditioning on the future states. Real-time inferences are drawn via a forward-filtering algorithm that operates on a virtually constructed discrete-time embedded Markov chain that mirrors the patient's continuous-time state trajectory. We demonstrate the prognostic utility of the HASMM in a critical care prognosis setting using a real-world dataset for patients admitted to the Ronald Reagan UCLA Medical Center. In particular, we show that using HASMMs, a patient's clinical deterioration can be predicted 8-9 hours prior to intensive care unit admission, with a 22% AUC gain compared to the Rothman index, which is the state-of-the-art critical care risk scoring technology.
GPS signal enhancement and attitude determination for a mini and low-cost unmanned aerial vehicle

We present in this paper an integration scheme of a low-cost inertial attitude and position reference system for a mini unmanned helicopter by utilizing the robust and H∞ filtering technique. The result has been successfully implemented and tested on our mini-scale unmanned helicopter. Simulation and flight experiment results show that the proposed technique is very effective in real-time and suitable for control, stabilization and navigation for mini-scale unmanned air vehicles.
APOLOGY AND COMPENSATION STRATEGY ON CUSTOMER FORGIVENESS AND NEGATIVE WORD OF MOUTH

The service provider could not totally guarantee the service process without any failure at all. This study aims to measure the influence of service recovery strategy towards customer forgiveness and negative word-of-mouth (WOM) as the effect of service failure. The service recovery strategy is performed in three types of vignette: apology, compensation, and apology-compensation. Vignette was given to 94 participants who have encountered service of airline. The result of ANOVA shows that apology compensation achieves the highest score relates to forgiveness. The interesting result of this study shows that even the customers forgive the service provider due to the service failure they did, this cannot diminish the intention of negative WOM. This study offers an implication to the company in order to pay attention regarding the compensation and the spread of negative WOM to the other customers
Critical role of the disintegrin metalloprotease ADAM17 for intestinal inflammation and regeneration in mice

The protease a disintegrin and metalloprotease (ADAM) 17 cleaves tumor necrosis factor (TNF), L-selectin, and epidermal growth factor receptor (EGF-R) ligands from the plasma membrane. ADAM17 is expressed in most tissues and is up-regulated during inflammation and cancer. ADAM17-deficient mice are not viable. Conditional ADAM17 knockout models demonstrated proinflammatory activities of ADAM17 in septic shock via shedding of TNF. We used a novel gene targeting strategy to generate mice with dramatically reduced ADAM17 levels in all tissues. The resulting mice called ADAM17ex/ex were viable, showed compromised shedding of ADAM17 substrates from the cell surface, and developed eye, heart, and skin defects as a consequence of impaired EGF-R signaling caused by failure of shedding of EGF-R ligands. Unexpectedly, although the intestine of unchallenged homozygous ADAM17ex/ex mice was normal, ADAM17ex/ex mice showed substantially increased susceptibility to inflammation in dextran sulfate sodium colitis. This was a result of impaired shedding of EGF-R ligands resulting in failure to phosphorylate STAT3 via the EGF-R and, consequently, in defective regeneration of epithelial cells and breakdown of the intestinal barrier. Besides regulating the systemic availability of the proinflammatory cytokine TNF, our results demonstrate that ADAM17 is needed for vital regenerative activities during the immune response. Thus, our mouse model will help investigate ADAM17 as a potential drug target.
Latent Structured Perceptrons for Large-Scale Learning with Hidden Information

Many real-world data mining problems contain hidden information (e.g., unobservable latent dependencies). We propose a perceptron-style method, latent structured perceptron, for fast discriminative learning of structured classification with hidden information. We also give theoretical analysis and demonstrate good convergence properties of the proposed method. Our method extends the perceptron algorithm for the learning task with hidden information, which can be hardly captured by traditional models. It relies on Viterbi decoding over latent variables, combined with simple additive updates. We perform experiments on one synthetic data set and two real-world structured classification tasks. Compared to conventional nonlatent models (e.g., conditional random fields, structured perceptrons), our method is more accurate on real-world tasks. Compared to existing heavy probabilistic models of latent variables (e.g., latent conditional random fields), our method lowers the training cost significantly (almost one order magnitude faster) yet with comparable or even superior classification accuracy. In addition, experiments demonstrate that the proposed method has good scalability on large-scale problems.