Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of atypical antipsychotics in the elderly: a clinical review

The use of atypical antipsychotic drugs in the elderly has become wider and wider in recent years; in fact, these agents have novel receptor binding profiles, good efficacy with regard to negative symptoms, and reduced extrapyramidal symptoms. However, in recent years, the use of both conventional and atypical antipsychotics has been widely debated for concerns about their safety in elderly patients affected with dementia and the possible risks for stroke and sudden death. A MEDLINE search was made using the words elderly, atypical antipsychotics, use, schizophrenia, psychosis, mood disorders, dementia, behavioral disorders, and adverse events. Some personal studies were also considered. This paper reports the receptor binding profiles and the main mechanism of action of these drugs, together with their main use in psychiatry and the possible adverse events in elderly people.
Inferring ideal amino acid interaction forms from statistical protein contact potentials

We have analyzed 29 different published matrices of protein pairwise contact potentials (CPs) between amino acids derived from different sets of proteins, either crystallographic structures taken from the Protein Data Bank (PDB) or computer‐generated decoys. Each of the CPs is similar to 1 of the 2 matrices derived in the work of Miyazawa and Jernigan (Proteins 1999;34:49–68). The CP matrices of the first class can be approximated with a correlation of order 0.9 by the formula eij = hi + hj, 1 ≤ i, j ≤ 20, where the residue‐type dependent factor h is highly correlated with the frequency of occurrence of a given amino acid type inside proteins. Electrostatic interactions for the potentials of this class are almost negligible. In the potentials belonging to this class, the major contribution to the potentials is the one‐body transfer energy of the amino acid from water to the protein environment. Potentials belonging to the second class can be approximated with a correlation of 0.9 by the formula eij = c0 − hihj + qiqj, where c0 is a constant, h is highly correlated with the Kyte–Doolittle hydrophobicity scale, and a new, less dominant, residue‐type dependent factor q is correlated (∼0.9) with amino acid isoelectric points pI. Including electrostatic interactions significantly improves the approximation for this class of potentials. While, the high correlation between potentials of the first class and the hydrophobic transfer energies is well known, the fact that this approximation can work well also for the second class of potentials is a new finding. We interpret potentials of this class as representing energies of contact of amino acid pairs within an average protein environment. Proteins 2005. © 2005 Wiley‐Liss, Inc.
SWATS: Wireless sensor networks for steamflood and waterflood pipeline monitoring

State-of-the-art anomaly detection systems deployed in oilfields are expensive, not scalable to a large number of sensors, require manual operation, and provide data with a long delay. To overcome these problems, we design a wireless sensor network system that detects, identifies, and localizes major anomalies such as blockage and leakage that arise in steamflood and waterflood pipelines in oilfields. A sensor network consists of small, inexpensive nodes equipped with embedded processors and wireless communication, which enables flexible deployment and close observation of phenomena without human intervention. Our sensor-network-based system, Steamflood and Waterflood Tracking System (SWATS), aims to allow continuous monitoring of the steamflood and waterflood systems with low cost, short delay, and fine-granularity coverage while providing high accuracy and reliability. The anomaly detection and identification is challenging because of the inherent inaccuracy and unreliability of sensors and the transient characteristics of the flows. Moreover, observation by a single node cannot capture the topological effects on the transient characteristics of steam and water fluid to disambiguate similar problems and false alarms. We address these hurdles by utilizing multimodal sensing and multisensor collaboration, and exploiting temporal and spatial patterns of the sensed phenomena.
Testing Wi-Fi and bluetooth low energy technologies for a hybrid indoor positioning system

Indoor positioning systems are becoming a required sub-system in many ambient assisted living scenarios. Also IoT (Internet of Things) device interaction would greatly benefit from the enriched context of localization. However, at this moment there is not a satisfying technology or approach for precise indoor positioning. In our paper we test the accuracy for Wi-Fi and Bluetooth Low Energy RSSI measurements and we propose a prototype system for smartphone simulation.
Understanding Popularity, Reputation, and Social Influence in the Twitter Society

The pervasive presence of online media in our society has transferred a significant part of political deliberation to online forums and social networking sites. This article examines popularity, reputation, and social influence on Twitter using large-scale digital traces from 2009 to 2016. We process network information on more than 40 million users, calculating new global measures of reputation that build on the D-core decomposition and the bow-tie structure of the Twitter follower network. We integrate our measurements of popularity, reputation, and social influence to evaluate what keeps users active, what makes them more popular, and what determines their influence. We find that there is a range of values in which the risk of a user becoming inactive grows with popularity and reputation. Popularity in Twitter resembles a proportional growth process that is faster in its strongly connected component, and that can be accelerated by reputation when users are already popular. We find that social influence on Twitter is mainly related to popularity rather than reputation, but that this growth of influence with popularity is sublinear. The explanatory and predictive power of our method shows that global network metrics are better predictors of inactivity and social influence, calling for analyses that go beyond local metrics like the number of followers.
Human Embryonic Stem Cells Develop Into Multiple Types of Cardiac Myocytes: Action Potential Characterization

Abstract— Human embryonic stem (hES) cells can differentiate in vitro, forming embryoid bodies (EBs) composed of derivatives of all three embryonic germ layers. Spontaneously contracting outgrowths from these EBs contain cardiomyocytes (CMs); however, the types of human CMs and their functional properties are unknown. This study characterizes the contractions and action potentials (APs) from beating EB outgrowths cultured for 40 to 95 days. Spontaneous and electrical field-stimulated contractions were measured with video edge-detection microscopy. &bgr;-Adrenergic stimulation with 1.0 &mgr;mol/L isoproterenol resulted in a significant increase in contraction magnitude. Intracellular electrical recordings using sharp KCl microelectrodes in beating EB outgrowths revealed three distinct classes of APs: nodal-like, embryonic atrial-like, and embryonic ventricular-like. The APs were described as embryonic based on the relatively depolarized resting membrane potential and slow AP upstroke. Repeated impalements of an individual beating outgrowth revealed a reproducible AP morphology recorded from different cells, suggesting that each outgrowth is composed of a predominant cell type. Complex functional properties typical of cardiac muscle were observed in the hES cell-derived CMs including rate adaptation of AP duration and provoked early and delayed afterdepolarizations. Repolarization of the AP showed a significant role for IKr based on E-4031 induced prolongation of AP duration as anticipated for human CMs. In conclusion, hES cells can differentiate into multiple types of CMs displaying functional properties characteristic of embryonic human cardiac muscle. Thus, hES provide a renewable source of distinct types of human cardiac myocytes for basic research, pharmacological testing, and potentially therapeutic applications.
Solving the Physical Traveling Salesman Problem: Tree Search and Macro Actions

This paper presents a number of approaches for solving a real-time game consisting of a ship that must visit a number of waypoints scattered around a 2-D maze full of obstacles. The game, the Physical Traveling Salesman Problem (PTSP), which featured in two IEEE conference competitions during 2012, provides a good balance between long-term planning (finding the optimal sequence of waypoints to visit), and short-term planning (driving the ship in the maze). This paper focuses on the algorithm that won both PTSP competitions: it takes advantage of the physics of the game to calculate the optimal order of waypoints, and it employs Monte Carlo tree search (MCTS) to drive the ship. The algorithm uses repetitions of actions (macro actions) to reduce the search space for navigation. Variations of this algorithm are presented and analyzed, in order to understand the strength of each one of its constituents and to comprehend what makes such an approach the best controller found so far for the PTSP.
Backhaul-Aware Interference Management in the Uplink of Wireless Small Cell Networks

The design of distributed mechanisms for interference management is one of the key challenges in emerging wireless small cell networks whose backhaul is capacity limited and heterogeneous (wired, wireless and a mix thereof). In this paper, a novel, backhaul-aware approach to interference management in wireless small cell networks is proposed. The proposed approach enables macrocell user equipments (MUEs) to optimize their uplink performance, by exploiting the presence of neighboring small cell base stations. The problem is formulated as a noncooperative game among the MUEs that seek to optimize their delay-rate tradeoff, given the conditions of both the radio access network and the - possibly heterogeneous - backhaul. To solve this game, a novel, distributed learning algorithm is proposed using which the MUEs autonomously choose their optimal uplink transmission strategies, given a limited amount of available information. The convergence of the proposed algorithm is shown and its properties are studied. Simulation results show that, under various types of backhauls, the proposed approach yields significant performance gains, in terms of both average throughput and delay for the MUEs, when compared to existing benchmark algorithms.
Sex Differences in Risk of Lung Cancer Associated with Methylene-tetrahydrofolate Reductase Polymorphisms

Methylenetetrahydrofolate reductase (MTHFR) catalyzes the metabolism of folate and nucleotides needed for DNA synthesis and repair. Variations in MTHFR functions likely play roles in the etiology of lung cancer. The MTHFR gene has three nonsynonymous single nucleotide polymorphisms (i.e., C677T, A1298C, and G1793A) that have a minor allele frequency of >5%. We investigated the associations between the frequencies of MTHFR variant genotypes and risk of lung cancer in a hospital-based case-control study of 1,051 lung cancer patients and 1,141 cancer-free controls in a non-Hispanic White population. We found that compared with the MTHFR 1298AA genotype, the 1298CC genotype was associated with a significantly increased risk of lung cancer in women [(odds ratio (OR), 2.09; 95% confidence interval (95% CI), 1.32-3.29)] but not in men (OR, 0.95; 95% CI, 0.62-1.45). The MTHFR 677TT genotype was associated with a significantly decreased risk of lung cancer in women (OR, 0.60; 95% CI, 0.40-0.92) but not in men. No association was found between the MTHFR G1793A polymorphism and risk of lung cancer. Further analysis suggested evidence of gene-dietary interactions between the MTHFR C677T polymorphism and dietary intake of vitamin B6, vitamin B12, and methionine in women and evidence of gene-environment interactions between the MTHFR C677T and A1298C polymorphisms and tobacco smoking in men. In conclusion, the polymorphisms of MTHFR may contribute to the risk of lung cancer in non-Hispanic Whites and modify the risk associated with the dietary and environmental exposure in a sex-specific manner.
Analysis and Design of Distributed Space–Time Trellis Codes With Amplify-and-Forward Relaying

We study the asymptotic behavior of a cooperative scheme operating in amplify-and-forward (AF) mode when the number of relay terminals tends to infinity. We consider three time-division-multiple-access-based cooperation protocols which realize different degrees of broadcasting and receive collision. Optimal design rules for distributed space-time codes (STCs) are derived through the investigation of pairwise error probability expression for each considered protocol. The derived design rules reveal a Euclidean-distance-type performance metric, including some scaling terms due to the effects of AF operation mode and cooperation protocols as well as path loss/shadowing effects associated with the underlying relay links. Based on the derived criteria, an exhaustive computer code search is conducted to find out optimal distributed STCs. Our search results indicate the optimality of conventional designs, i.e., based on classical Euclidean distance, for relay numbers larger than two in a distributed scenario. For the special cases of one and two relays, we present novel distributed codes which are able to outperform their conventional counterparts and demonstrate robustness against distributed implementation.
MIMO experiment design based on asymptotic model order theory

In this paper we investigate the problem of designing an input signal for a multi-input multi-output plant to minimize a control-oriented criterion. By employing Ljung's asymptotic (in model order and sample size) covariance formulas, we determine closed form expressions for the optimal input, which provide direct insight into the effect of the principal directions and gains of the open- and closed-loop transfer functions on the kind of experiment to be applied.
Genomic damage as a biomarker of chronic kidney disease status

Patients suffering from chronic kidney disease (CKD) exhibit a high incidence of cancer and cardiovascular diseases, as well as high levels of genomic damage. To confirm the association of CKD with genomic damage we have carried out the largest study to date addressing this issue, using a total of 602 subjects (187 controls, 206 pre‐dialysis CKD patients and 209 CKD patients in hemodialysis). DNA oxidative damage was measured in all individuals using the comet assay. Our results indicate that CKD patients have significantly higher levels of DNA damage than controls, but no significant differences were observed between pre‐hemodialysis (pre‐HD) and hemodialysis (HD) patients. When oxidative damage was measured, no differences were observed between patients and controls, although HD patients showed significantly higher levels of oxidative damage than pre‐HD patients. In addition, a positive relationship was demonstrated between genomic damage and all‐cause mortality. Our study confirms that genomic damage can be predictive of prognosis in CKD patients, with high levels of DNA damage indicating a poor prognosis in HD patients. Environ. Mol. Mutagen. 56:301–312, 2015. © 2014 Wiley Periodicals, Inc.
Brain-Targeted Proanthocyanidin Metabolites for Alzheimer's Disease Treatment

While polyphenolic compounds have many health benefits, the potential development of polyphenols for the prevention/treatment of neurological disorders is largely hindered by their complexity as well as by limited knowledge regarding their bioavailability, metabolism, and bioactivity, especially in the brain. We recently demonstrated that dietary supplementation with a specific grape-derived polyphenolic preparation (GP) significantly improves cognitive function in a mouse model of Alzheimer's disease (AD). GP is comprised of the proanthocyanidin (PAC) catechin and epicatechin in monomeric (Mo), oligomeric, and polymeric forms. In this study, we report that following oral administration of the independent GP forms, only Mo is able to improve cognitive function and only Mo metabolites can selectively reach and accumulate in the brain at a concentration of ∼400 nm. Most importantly, we report for the first time that a biosynthetic epicatechin metabolite, 3′-O-methyl-epicatechin-5-O-β-glucuronide (3′-O-Me-EC-Gluc), one of the PAC metabolites identified in the brain following Mo treatment, promotes basal synaptic transmission and long-term potentiation at physiologically relevant concentrations in hippocampus slices through mechanisms associated with cAMP response element binding protein (CREB) signaling. Our studies suggest that select brain-targeted PAC metabolites benefit cognition by improving synaptic plasticity in the brain, and provide impetus to develop 3′-O-Me-EC-Gluc and other brain-targeted PAC metabolites to promote learning and memory in AD and other forms of dementia.
Social Workers Reflect on Engagement with Involuntary Clients

For social workers, engagement refers to the process through which clients become active and involved in their treatment. Involuntary clients, or clients who are legally mandated or feel pressure to seek treatment, struggle with engagement and are often viewed as being resistant. This study examined the engagement process through interviews conducted with social workers who have experience in working with involuntary clients. Five social workers discussed the engagement process and strategies they use to encourage the engagement process with involuntary clients. They emphasized the importance of giving the clients choice and control over their treatment, and having the capacity to genuinely like the client. Motivational interviewing and relational approaches were cited as beneficial for fostering engagement with involuntary clients, a view that is consistent with previous research.
West Nile virus disease in children.

West Nile virus (WNV) is transmitted to children primarily by the bite of infected mosquitoes, but can be acquired through blood transfusion, organ transplantation, congenitally and possibly breast-feeding. WNV is an enveloped RNA flavivirus (named after the group’s prototypic yellow fever virus) in the same serocomplex as Japanese, St. Louis and Murray Valley encephalitis viruses. WNV is thought to replicate in dendritic cells and then spread to lymph nodes and blood. About 80% of infected people remain asymptomatic, 20% develop West Nile fever (WNF) and 1% develop neuroinvasive disease. Although the risk of WNV infection may be higher in children than in adults, children have a lower risk of developing neuroinvasive disease. The incubation period ranges from 2 to 14 days after inoculation. WNV transmission occurs in much of southern Asia, Africa, the Middle East and Europe. In 1999, the virus was first detected in the eastern United States and has since spread across North America. Only rare cases of human disease have been reported thus far from Latin America and the Caribbean. From 1999 through 2005, a total of 1177 children younger than 19 years old with WNV disease and 3 childhood fatalities, ages 1 month, 14 years and 15 years, were reported in the United States. During 2004 and 2005, 261 cases were reported: 50 with encephalitis, 54 with meningitis, 136 with WNF (WNF cases are disproportionately underreported) and 21 with other or unknown presentations. Five of the 261 children were reported to have flaccid paralysis.
Position paper: why are there so many vulnerabilities in web applications?

As the Web has become more and more ubiquitous, the number of attacks on web applications have increased substantially. According to a recent report, over 80 percent of web applications have had at least one serious vulnerability. This percentage is alarmingly higher than traditional applications. Something must be fundamentally wrong in the web infrastructure. Based on our research, we have formulated the following position: when choosing the stateless framework for the Web, we ignored a number of security properties that are essential to applications. As a result, the Trusted Computing Base(TCB) of the Web has significant weaknesses. To build secure stateful applications on top of a weakened TCB, developers have to implement extra protection logic in their web applications, making development difficult and error prone, and thereby causing a number of security problems in web applications. In this paper, we will present evidence, justification, and in-depth analysis to support this position.
Ontology Verification Using Contexts

Ontologies have become the de-facto modeling tool of choice, used in a variety of applications and prominently in the Semantic Web. Their design and maintenance, nevertheless, have been and still are a daunting task. As a result, ontologies quickly become underspecified. Therefore, if ontologies do not evolve, the semantic infrastructure of the information system can no longer support the changing needs of the organization. In this work we provide a model to semi-automatically support relationship evolution in an ontology using contexts. We propose to use (machine-generated) contexts as a mechanism for quantifying relationships among concepts. To do so we compare the contexts that are associated with the ontology constructs. On a conceptual level, we introduce an ontology verification model, a quantified model for automatically assessing the validity of relationships in an ontology. We motivate our work with examples from the field of eGovernment applications. To support our model with an empirical analysis, we provide a mapping of an ontology operator for defining relationships into context relationships, using real-world traces of RSS.
BORDER: efficient computation of boundary points

This work addresses the problem of finding boundary points in multidimensional data sets. Boundary points are data points that are located at the margin of densely distributed data such as a cluster. We describe a novel approach called BORDER (a BOundaRy points DEtectoR) to detect such points. BORDER employs the state-of-the-art database technique - the Gorder kNN join and makes use of the special property of the reverse k nearest neighbor (RkNN). Experimental studies on data sets with varying characteristics indicate that BORDER is able to detect the boundary points effectively and efficiently.