Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase 3 trials of solanezumab for mild-to-moderate Alzheimer's disease.

BACKGROUND Alzheimer's disease is characterized by amyloid-beta plaques, neurofibrillary tangles, gliosis, and neuronal loss. Solanezumab, a humanized monoclonal antibody, preferentially binds soluble forms of amyloid and in preclinical studies promoted its clearance from the brain. METHODS In two phase 3, double-blind trials (EXPEDITION 1 and EXPEDITION 2), we randomly assigned 1012 and 1040 patients, respectively, with mild-to-moderate Alzheimer's disease to receive placebo or solanezumab (administered intravenously at a dose of 400 mg) every 4 weeks for 18 months. The primary outcomes were the changes from baseline to week 80 in scores on the 11-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog11; range, 0 to 70, with higher scores indicating greater cognitive impairment) and the Alzheimer's Disease Cooperative Study-Activities of Daily Living scale (ADCS-ADL; range, 0 to 78, with lower scores indicating worse functioning). After analysis of data from EXPEDITION 1, the primary outcome for EXPEDITION 2 was revised to the change in scores on the 14-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog14; range, 0 to 90, with higher scores indicating greater impairment), in patients with mild Alzheimer's disease. RESULTS Neither study showed significant improvement in the primary outcomes. The modeled difference between groups (solanezumab group minus placebo group) in the change from baseline was -0.8 points for the ADAS-cog11 score (95% confidence interval [CI], -2.1 to 0.5; P=0.24) and -0.4 points for the ADCS-ADL score (95% CI, -2.3 to 1.4; P=0.64) in EXPEDITION 1 and -1.3 points (95% CI, -2.5 to 0.3; P=0.06) and 1.6 points (95% CI, -0.2 to 3.3; P=0.08), respectively, in EXPEDITION 2. Between-group differences in the changes in the ADAS-cog14 score were -1.7 points in patients with mild Alzheimer's disease (95% CI, -3.5 to 0.1; P=0.06) and -1.5 in patients with moderate Alzheimer's disease (95% CI, -4.1 to 1.1; P=0.26). In the combined safety data set, the incidence of amyloid-related imaging abnormalities with edema or hemorrhage was 0.9% with solanezumab and 0.4% with placebo for edema (P=0.27) and 4.9% and 5.6%, respectively, for hemorrhage (P=0.49). CONCLUSIONS Solanezumab, a humanized monoclonal antibody that binds amyloid, failed to improve cognition or functional ability. (Funded by Eli Lilly; EXPEDITION 1 and 2 ClinicalTrials.gov numbers, NCT00905372 and NCT00904683.).
Decentralized Localization of Sparsely-Communicating Robot Networks: A Centralized-Equivalent Approach

Finite-range sensing and communication are factors in the connectivity of a dynamic mobile-robot network. State estimation becomes a difficult problem when communication connections allowing information exchange between all robots are not guaranteed. This paper presents a decentralized state-estimation algorithm guaranteed to work in dynamic robot networks without connectivity requirements. We prove that a robot only needs to consider its own knowledge of network topology in order to produce an estimate equivalent to the centralized state estimate whenever possible while ensuring that the same can be performed by all other robots in the network. We prove certain properties of our technique and then it is validated through simulations. We present a comprehensive set of results, indicating the performance benefit in different network connectivity settings, as well as the scalability of our approach.
Multi-class HingeBoost

Summary Background: Multi-class molecular cancer classification has great potential clinical implications. Such applications require statistical methods to accurately classify cancer types with a small subset of genes from thousands of genes in the data. Objectives: This paper presents a new functional gradient descent boosting algorithm that directly extends the HingeBoost algorithm from the binary case to the multi-class case without reducing the original problem to multiple binary problems. Methods: Minimizing a multi-class hinge loss with boosting technique, the proposed Hinge-Boost has good theoretical properties by implementing the Bayes decision rule and providing a unifying framework with either equal or unequal misclassification costs. Furthermore, we propose Twin HingeBoost which has better feature selection behavior than Hinge-Boost by reducing the number of ineffective covariates. Simulated data, benchmark data and two cancer gene expression data sets are utilized to evaluate the performance of the proposed approach. Results: Simulations and the benchmark data showed that the multi-class HingeBoost generated accurate predictions when compared with the alternative methods, especially with high-dimensional covariates. The multi-class Hinge-Boost also produced more accurate prediction or comparable prediction in two cancer classification problems using gene expression data. Conclusions: This work has shown that the HingeBoost provides a powerful tool for multi-classification problems. In many applications, the classification accuracy and feature selection behavior can be further improved when using Twin HingeBoost.
Proof-Carrying Data and Hearsay Arguments from Signature Cards

Design of secure systems can often be expressed as ensuring that some property is maintained at every step of a distributed computation among mutually-untrusting parties. Special cases include integrity of programs running on untrusted platforms, various forms of confidentiality and side-channel resilience, and domain-specific invariants. We propose a new approach, proof-carrying data (PCD), which circumnavigates the threat of faults and leakage by reasoning about properties of the output data, independently of the preceding computation. In PCD, the system designer prescribes the desired properties of the computation’s outputs. Corresponding proofs are attached to every message flowing through the system, and are mutually verified by the system’s components. Each such proof attests that the message’s data and all of its history comply with the specified properties. We construct a general protocol compiler that generates, propagates and verifies such proofs of compliance, while preserving the dynamics and efficiency of the original computation. Our main technical tool is the cryptographic construction of short non-interactive arguments (computationally-sound proofs) for statements whose truth depends on “hearsay evidence”: previous arguments about other statements. To this end, we attain a particularly strong proof of knowledge. We realize the above, under standard cryptographic assumptions, in a model where the prover has blackbox access to some simple functionality — essentially, a signature card.
Markov Chains , Iterated System of Functions and Coupling time for Perfect Simulation

Simulation of Markov chains are usually based on an algorithmic representation of the chain. This corresponds to stochastic recurrent equation and could be interpreted as random iterated systems of functions (RIFS). In particular, for perfect simulation of Markov chains, the RIFS structure has a deep impact on execution time of the simulation. Links between the structure of the RIFS and coupling time of algorithm are detailed in this paper. Conditions for coupling and upper bound for simulation time are given for Doeblin matrices. Finally, it is shown that aliasing techniques build an RIFS with a particular binary structure.
Flavonoids: a metabolic network mediating plants adaptation to their real estate

From an evolutionary perspective, the emergence of the sophisticated chemical scaffolds of flavonoid molecules represents a key step in the colonization of Earth’s terrestrial environment by vascular plants nearly 500 million years ago. The subsequent evolution of flavonoids through recruitment and modification of ancestors involved in primary metabolism has allowed vascular plants to cope with pathogen invasion and damaging UV light. The functional properties of flavonoids as a unique combination of different classes of compounds vary significantly depending on the demands of their local real estate. Apart from geographical location, the composition of flavonoids is largely dependent on the plant species, their developmental stage, tissue type, subcellular localization, and key ecological influences of both biotic and abiotic origin. Molecular and metabolic cross-talk between flavonoid and other pathways as a result of the re-direction of intermediate molecules have been well investigated. This metabolic plasticity is a key factor in plant adaptive strength and is of paramount importance for early land plants adaptation to their local ecosystems. In human and animal health the biological and pharmacological activities of flavonoids have been investigated in great depth and have shown a wide range of anti-inflammatory, anti-oxidant, anti-microbial, and anti-cancer properties. In this paper we review the application of advanced gene technologies for targeted reprogramming of the flavonoid pathway in plants to understand its molecular functions and explore opportunities for major improvements in forage plants enhancing animal health and production.
How Business Analytics Systems Provide Benefits and Contribute to Firm Performance?

Organisations invest in Business analytics (BA) systems to improve firm performance and gain competitive advantage. BA systems use advanced analytical tools and techniques to analyse organisational data and generate insights. Decision makers at different levels of the organisations leverage the insights and take competitive actions. In this paper, we utilise Resource-based View (RBV) and business value of IT literature to develop a research model to explain the firm performance impacts of BA systems in customer relations. The research model proposes that BA capability creates informational benefits in customer relations using two pathways: (1) Direct creation of informational benefits, and (2) Indirect creation of informational benefits through developing higher-order Analytical CRM capability. Informational benefits once created, contribute to superior firm performance. The research model is evaluated using survey data in Large US-based organisations.
Political information and motivation: A case of reciprocal causality?

Political knowledge has been shown to influence a host of substantively important outcomes, such as participation, issue preference and vote choice. The causes of individual heterogeneity in knowledge have gone relatively unexplored however. What leads some individuals to become political sophisticates and others not? Generally, motivation has been considered as key in this regard; those who are interested in politics seek out and retain political information which leads, in turn, to higher levels of interest in politics. Using data from the 1992-1997 and 1997-2001 British Election Panel Studies, however, we find no evidence of a reciprocal effects mechanism. Although this ‘virtuous circle’ model of sophistication has accrued some empirical support in the US, with British data we find evidence only for a uni-directional effect from interest to knowledge. We argue that previous analyses are potentially flawed due to their reliance on cross-sectional data and likely violation of model assumptions.
An Embedded and Programmable System Based FPGA for Real Time MPEG Stream Buffer Analysis

The MPEG transport stream is an extremely complex structure using interlinked tables and coded identifiers to separate the programs and the elementary streams. Quality management is therefore a complicated issue and the need to identify the degree of coding degradations in terms of coding and/or transmission errors or system failures is becoming an important criterion for the evaluation of the quality of the MPEG streams. A theoretical decoder (T-STD) defines the verification process based on the proper fill level of an MPEG decoder buffers whose size is defined by the standards in order to obtain an evaluation of the MPEG stream quality. This paper describes a new embedded and programmable solution capable of analysing MPEG streams in real time. The proposed hardware architecture provides a real time continuous buffer analysis of the MPEG stream components and is composed of several modules allowing for simultaneous modeling of the various buffers of the T-STD components (video, audio or system). Real time errors flags are generated when the buffers filling level becomes illegal (overflow, empty buffer, transfer delay, etc.). The architecture has been modeled, validated and simulated using the SystemC and VHDL languages in combination with real MPEG DVB-T streams. A VHDL synthesisable model of our architecture allows an implementation on an field-programmable gate array circuit based on Altera APEX20K1000. The hardware implementation of this configurable T-STD allows a data rate of 232 Mbps and requires only 9738 logical cells and 4,7 kB memory.
Combination of measurements of the top-quark pair production cross section from the Tevatron Collider

We combine six measurements of the inclusive top-quark pair (ttbar) production cross section (sigma_ttbar) from data collected with the CDF and D0 detectors at the Fermilab Tevatron with proton anti-proton collisions at sqrt{s} = 1.96 TeV. The data correspond to integrated luminosities of up to 8.8 fb^{-1}. We obtain a value of sigma_ttbar = 7.60 \pm 0.41 pb for a top-quark mass of m_t=172.5 GeV. The contributions to the uncertainty are 0.20 pb from statistical sources, 0.29 pb from systematic sources, and 0.21 pb from the uncertainty on the integrated luminosity. The result is in good agreement with the standard model expectation of 7.35^{+0.28}_{-0.33} pb at NNLO+NNLL in pertubative QCD.
The Effect of Sample Storage on Total Cholesterol and Hdl-cholesterol Assays

The result of sample analysis is said to be as good as the sample collection and preparation. Without adequate sample handling, accuracy and precision of sample analysis will be greatly affected. The effect of sample storage temperature and length of storage time on serum total cholesterol (TC) and HDL-cholesterol (HDL-C) assays was studied using twenty different samples, pooled into three. Each pool was split into three and stored at different temperatures- room temperature (16 - 25 °C), refrigerator (4 °C) and freezer temperature (-20 °C), for 6, 30 ad 51 days respectively. The observations from the results obtained using day zero as control showed that the TC concen tration in the samples stored at room temperature increased with the length of storage time. However, these increases were not statistically significant (P>0.05), for the duration of the study. HDL-C concentration was found to be significantly increased (p=0.0211 and 0.0117) from day 2 and 10, at room and refrigerator temp eratures respe ctively. Ho wever, there w as no statistically significant difference (P>0.05) in the samples stored at freezer temperature in both TC and HDL-C concentrations. Except for the TC concentration in the sample stored at freezer temperature, the samples showed a significant correlation at room, refrigerator and freezer te mperatures respec tively with the durat ion of s torage. From this study, it can be concluded that the concentrations of TC and HDL-C in stored samples are both time and temperature dependent. Also, the concentr ation is mostl y affect ed at room temperature and least af fected at freezer temperature. Hence, i f s amples f or TC and HDL- C a ssays are to b e stored , freeze r temp erature is highly preferred.
Titin, a Central Mediator for Hypertrophic Signaling, Exercise-Induced Mechanosignaling and Skeletal Muscle Remodeling

Titin is a giant scaffold protein with multiple functions in striated muscle physiology. Due to the elastic I-band domains and the filament-like integration in the half-sarcomere titin is an important factor for sarcomere assembly and serves as an adaptable molecular spring that determines myofilament distensibility. Protein-interactions e.g., with muscle ankyrin repeat proteins or muscle LIM-protein link titin to hypertrophic signaling and via p62 and Muscle Ring Finger proteins to mechanisms that control protein quality control. This review summarizes our current knowledge on titin as a central node for exercise-induced mechanosignaling and remodeling and further highlights the pathophysiological implications.
Possible involvement of GABAergic modulation in the protective effect of gabapentin against immobilization stress‐induced behavior alterations and oxidative damage in mice

Introduction Acute stress may be experienced in response to an immediate physical, emotional or psychological stimulus. Stress has been known to affect several brain activities and promote long‐term changes in multiple neural systems. In the present study, we investigated the possible involvement of GABAergic modulation in the protective effect of gabapentin in acute immobilization‐induced behavioral alterations and oxidative damage in mice.
Clinical characteristics, treatment and survival outcomes in malignant mesothelioma: eighteen years' experience in Turkey.

BACKGROUND Malignant mesothelioma (MM) is an insidious tumor with poor prognosis, arising from mesothelial surfaces such as pleura, peritoneum and pericardium. We here aimed to evaluate the demographic, clinical, and radiological features of patients with MM followed in our center as well as their survival. METHODS The study included 228 patients (131 male, 97 female) who were followed up in our institution between 1993 and 2010 with the diagnosis of MM. RESULTS The mean age was 59.1 years in men and 58.7 years in women and the sex ratio was 1.4:1 in favor of males. Environmental asbestos exposure was present in 86% of the patients for a mean duration of 40±20 years (range: 3-70). Pleural effusion and thoracic/abdominal pain were the most common presenting signs and symptoms (70.2% and 57.8%, respectively). One hundred-thirteen (66%) patients were treated with platinum-based combination chemotherapy (PBCT) plus supportive care (SC) and 67 (34%) patients received SC alone. The median follow-up time was 10.0 months. The median overall survival was significantly improved with PBCT plus SC compared to SC alone (11.4 vs. 5.1 months; p=0.005). The 6, 12, 18, and 24-month survival rates were significantly improved with PBCT plus SC compared to SC alone (72%, 43%, 19%, and 2% vs. 49%, 31%, 11%, and 1%). CONCLUSION The survival of patients with MM improved in patients treated with PBCT. The survival advantage continued 12- and 24-month after the initial time of combination chemotherapy.
Pericranial Tenderness in Tension Headache: A Blind, Controlled Study

Forty patients with tension headache and 40 healthy comparable control persons were palpated by the same “blinded” observer. Tenderness in 10 pericranial muscles on each side was rated on a four-point scale. A Total Tenderness Score was calculated for each individual by adding the scores from all palpated areas. Headache patients had significantly higher scores than controls and also significantly higher tenderness in each point separately. Median normal values and confidence limits for tenderness are given. Among 23 patients with daily headache a correlation was found between headache intensity and Total Tenderness Score. It is likely that the pathologic tenderness in patients with tension headache is the source of nociception, but pain mechanisms are more complex, as evidenced by discrepancy between tenderness and pain in some patients. Pathologic tenderness should be a contributing criterion to the diagnosis of tension headache (muscle conctraction headache).
SEQUENTIAL REPLICATION OF THE BACILLUS SUBTILIS CHROMOSOME. 3. REGULATION OF INITIATION.

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Intranasal monoclonal IgA antibody to respiratory syncytial virus protects rhesus monkeys against upper and lower respiratory tract infection.

Respiratory syncytial virus (RSV), the major cause of lower respiratory tract disease in infants, is thought to infect the upper airways before spreading to the lower respiratory tract. A rhesus monkey model of RSV infection after upper airway inoculation was used to test the protective effect of intranasal treatment with HNK20, a mouse monoclonal IgA antibody against RSV F glycoprotein. HNK20 was administered once daily for 2 days before RSV challenge and 4 days after challenge. Treatment with 0.5 mg/kg HNK20 reduced viral shedding in the nose, throat, and lungs by 3-4 log10/mL (P < or = .002). All monkeys developed RSV neutralizing antibody in serum, even in the absence of detectable viral replication. Neutralizing concentrations of monoclonal antibody remained in nasal secretions for > 1 day after treatment. These results suggest that nose-drop application of monoclonal antibody could provide convenient and effective protection against RSV infection in human infants at risk of severe lower respiratory tract disease.
A Classification-based Cocktail-party Processor

At a cocktail party, a listener can selectively attend to a single voice and filter out other acoustical interferences. How to simulate this perceptual ability remains a great challenge. This paper describes a novel supervised learning approach to speech segregation, in which a target speech signal is separated from interfering sounds using spatial location cues: interaural time differences (ITD) and interaural intensity differences (IID). Motivated by the auditory masking effect, we employ the notion of an ideal time-frequency binary mask, which selects the target if it is stronger than the interference in a local time-frequency unit. Within a narrow frequency band, modifications to the relative strength of the target source with respect to the interference trigger systematic changes for estimated ITD and IID. For a given spatial configuration, this interaction produces characteristic clustering in the binaural feature space. Consequently, we perform pattern classification in order to estimate ideal binary masks. A systematic evaluation in terms of signal-to-noise ratio as well as automatic speech recognition performance shows that the resulting system produces masks very close to ideal binary ones. A quantitative comparison shows that our model yields significant improvement in performance over an existing approach. Furthermore, under certain conditions the model produces large speech intelligibility improvements with normal listeners.