Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationships Between Caregiver Stress and Self-Care Behaviors in Response to Symptoms

The specific aims of this study were to (a) identify relationships among care-giving stress, caregivers’ functional ability, and number of self-care behavior responses to physical and psychological symptoms in caregivers of persons with dementia and (b) examine the mediating function of functional ability in the relationship between caregiving stress and self-care behavior response to symptoms. A correlational, cross-sectional design was used, and a survey was mailed to 99 caregivers. The survey questionnaire contained items about demographics, caregiving stress, functional ability, and self-care behavior. The results indicate that caregivers who reported higher levels of caregiving stress had poorer self-rated health, poorer physical function, more symptoms, high levels of depressed mood, and more self-care behaviors. Caregiving stress was indirectly related to self-care behavior response to symptoms through functional ability, which suggests a need for developing early interventions to enhance the functional ability and self-care behaviors in response to some caregivers’ symptoms.
Selecting Nodes and Buying Links to Maximize the Information Diffusion in a Network

The Independent Cascade Model (ICM) is a widely studied model that aims to capture the dynamics of the information diffusion in social networks and in general complex networks. In this model, we can distinguish between active nodes which spread the information and inactive ones. The process starts from a set of initially active nodes called seeds. Recursively, currently active nodes can activate their neighbours according to a probability distribution on the set of edges. After a certain number of these recursive cycles, a large number of nodes might become active. The process terminates when no further node gets activated. Starting from the work of Domingos and Richardson, several studies have been conducted with the aim of shaping a given diffusion process so as to maximize the number of activated nodes at the end of the process. One of the most studied problems has been formalized by Kempe et al. and consists in finding a set of initial seeds that maximizes the expected number of active nodes under a budget constraint. In this paper we study a generalization of the problem of Kempe et al. in which we are allowed to spend part of the budget to create new edges incident to the seeds. That is, the budget can be spent to buy seeds or edges according to a cost function. The problem does not admin a PTAS, unless $P=NP$. We propose two approximation algorithms: the former one gives an approximation ratio that depends on the edge costs and increases when these costs are high; the latter algorithm gives a constant approximation guarantee which is greater than that of the first algorithm when the edge costs can be small.
Mining sequential patterns including time intervals

We introduce the problem of mining sequential patterns among items in a large database of sequences. For example, let us consider a database recording storm patterns, in such an area, at such a given time. An example of the patterns we are interested in is: '10% of storms go through area C 3 days after they strike areas A and B. ' Previous research would have considered some equivalent patterns, but such work would use only 'after' (a succession in time) and omit '3 days after' (a period). Obtaining such patterns is very useful because we know when actions should be taken. To address this issue, we are studying an algorithm for discovering ordered lists of itemsets (a sets of items) with the time intervals between itemsets that occur in a sufficient number of sequences of transactions, we call these patterns 'delta pattern. ' In this algorithm, we cluster time intervals between two neighboring itemsets using the CF-tree method while scanning the database and counting the number of occurrences of each candidate pattern. Extensive simulations are being conducted to evaluate patterns and to discover the power and performance of this algorithm. This algorithm has very good scale-up properties in execution time with respect to the number of data-sequences.
Readability Classification for German using Lexical, Syntactic, and Morphological Features

We investigate the problem of reading level assessment for German texts on a newly compiled corpus of freely available easy and difficult articles, targeted at adult and child readers respectively. We adapt a wide range of syntactic, lexical and language model features from previous research on English and combined them with new features that make use of the rich morphology of German. We show that readability classification for German based on these features is highly successful, reaching 89.7% accuracy, with the new morphological features making an important contribution.
DIAGNOSIS OF EPILEPSY AFTER A FIRST UNPROVOKED SEIZURE: THE DIFFERENT ASPECTS OF A SINGLE PROBLEM

Despite several studies there are still some issues concerning the correct diagnosis of epilepsy that should be distinguished from many other critical symptoms and diseases. Moreover, the assessment of a specific epileptic syndrome can have some degree of uncertainty. In this research highlight we discussed the findings of our recent study that demonstrated that at the onset of seizures an initial diagnosis is possible in the majority of cases; epilepsy syndromes can be identified at the time of the initial diagnosis and, at follow up, this diagnosis has not to be revised in 90% of the cases. Moreover, we analysed the main data form literature concerning the difficulties of the epilepsy syndromes diagnosis
Automatic generation of VHDL for controller of inverted pendulum in consideration of robustness

In this study, to automate electronic controller design, we apply evolutionary computation, starting with the targeted inverted pendulum and task definition, followed by the framework of applying a genetic algorithm to controller design automation, focusing on its robustness. We use complex programmable logic device (CPLD) for the controller data processing, and optimize very-high-speed integrated circuit hardware description language (VHDL), which describes the logical circuit in CPLD as the controller, using evolutionary computation. We present the fitness function we use to develop the controller automatically. Evolutionary simulation verified the feasibility of our framework.
Distribution of aminoglycoside resistance genes in recent clinical isolates of Enterococcus faecalis, Enterococcus faecium and Enterococcus avium

Aminoglycoside modifying enzymes (AMEs) are major factors which confer aminoglycoside resistance on bacteria. Distribution of genes encoding seven AMEs was investigated by multiplex PCR for 279 recent clinical isolates of enterococci derived from a university hospital in Japan. The aac(6′)-aph(2″), which is related to high level gentamicin resistance, was detected at higher frequency in Enterococcus faecalis (42·5 %) than in Enterococcus faecium (4·3 %). Almost half of E. faecalis and E. faecium isolates possessed ant(6)-Ia and aph(3′)-IIIa. The profile of AME gene(s) detected most frequently in individual strains of E. faecalis was aac(6′)-aph(2″)+ant(6)-Ia+aph(3′)-IIIa, and isolates with this profile showed high level resistance to both gentamicin and streptomycin. In contrast, AME gene profiles of aac(6′)-Ii+ant(6)-Ia+aph(3′)-IIIa, followed by aac(6′)-Ii alone, were predominant in E. faecium. Only one AME gene profile of ant(6)-Ia+aph(3′)-IIIa was found in Enterococcus avium. The ant(4′)-Ia and ant(9)-Ia, which have been known to be distributed mostly among Staphylococcus aureus strains, were detected in a few enterococcal strains. An AME gene aph(2″)-Ic was not detected in any isolates of the three enterococcal species. These findings indicated a variety of distribution profiles of AME genes among enterococci in our study site.
Guesswork and entropy

We derive the moments of the guesswork , the number of attempts required to correctly guess the output of a random source, for a source determined by a Markov chain via a large deviations type estimate. These moments are related to the Perron-Frobenius eigenvalue of the matrix formed by element-wise powers of the Markov chain's transition matrix.
Vision-based altitude and pitch estimation for ultra-light indoor microflyers

Autonomous control of ultra-light indoor microflyers is a difficult and largely unsolved task because of the strong limitations on the kind of sensors that can be embedded. We propose a new approach for altitude control of a 10-gram microflyer, where altitude as well as pitch angle are estimated using a set of visual, airspeed and gyroscopic sensors that weight about 1 (g) in total. This approach does not rely on an explicit estimation of optic flow, but rather takes as input the raw images as provided by the vision sensor. We show that altitude and pitch angle of a simulated agent can be successfully estimated. This result is thus a first step toward autonomous altitude control of indoor flying robots
Efficient polarization of high-angular-momentum systems

We present a novel technique of efficient optical pumping of open, high-angular-momentum systems. The method combines two well-established approaches of population manipulation (conventional optical pumping and coherent population transfer), offering the ability to achieve higher population of a sublevel with the highest or lowest quantum number m (the “end state”) than obtainable with either of the techniques. To accomplish this task, we propose to use coherent-population-transfer technique (e.g., adiabatic fast passage) to arrange the system in such a way that spontaneously emitted photon (conventional optical pumping) carries away more entropy than in conventional schemes. This enables reduction of a number of spontaneous decays Nsd required to pump the system with the total angular momentum J from Nsd = J decays in the conventional scheme to Nsd ≲ log2(2J) decays in the proposed scheme. Since each spontaneous-emission event is potentially burdened with a loss of population (population is transferred to a dark state), this enables increasing population accumulated in the “end state”, which is important for many applications.
Special Issue on Semantic Web Interfaces

Roberto Garcia a, Heiko Paulheim b and Paola Di Maio c a Computer Science and Engineering Department, Universitat de Lleida, C / Jaume II, 69, 25001 Lleida, Spain E-mail: roberto.garcia@udl.cat b Data and Web Science Group, University of Mannheim, B6 26, 68159 Mannheim, Germany E-mail: heiko@informatik.uni-mannheim.de c Universal Interfaces Research Lab, ISTCS, 1 Summerhall, Edinburgh EH9 1PL, UK E-mail: paola.dimaio@gmail.com
The levels of analysis revisited

The term levels of analysis has been used in several ways: to distinguish between ultimate and proximate levels, to categorize different kinds of research questions and to differentiate levels of reductionism. Because questions regarding ultimate function and proximate mechanisms are logically distinct, I suggest that distinguishing between these two levels is the best use of the term. Integrating across levels in research has potential risks, but many benefits. Consideration at one level can help generate novel hypotheses at the other, define categories of behaviour and set criteria that must be addressed. Taking an adaptationist stance thus strengthens research on proximate mechanisms. Similarly, it is critical for researchers studying adaptation and function to have detailed knowledge of proximate mechanisms that may constrain or modulate evolutionary processes. Despite the benefits of integrating across ultimate and proximate levels, failure to clearly identify levels of analysis, and whether or not hypotheses are exclusive alternatives, can create false debates. Such non-alternative hypotheses may occur between or within levels, and are not limited to integrative approaches. In this review, I survey different uses of the term levels of analysis and the benefits of integration, and highlight examples of false debate within and between levels. The best integrative biology reciprocally uses ultimate and proximate hypotheses to generate a more complete understanding of behaviour.
Bespoke microbiome therapy to manage plant diseases

Information gathered with advanced nucleotide sequencing technologies, small molecule detection systems and computational biology is revealing that a community of microbes and their genes, now termed “the microbiome,” located in gut and rhizosphere, is responsible for maintaining the health of human beings and plants, respectively. Within the complete microbiome a “core-microbiome” exists that plays the pivotal role in well being of humans and plants. Recent studies in medicine have shown that an artificial mixture of bacteria representing the core gut microbiome of healthy person when transferred into gut of diseased person results in re-establishment of normal microflora in the latter leading to alleviation from diseased condition. In agriculture, though not exactly in similar manner as in medicine, success in plant disease management has been achieved through transfer of microbiome by mixing disease suppressive soils with disease conducive soils. A study more similar to artificial gut microbiome transfer in medical field has been recently reported in agriculture, in which transfer of microbiome via soil solutions (filtered and unfiltered) has shown ability to alleviate drought stress in Arabidopsis thaliana. However, the exact practice of transferring artificially cultivated core-microbiome as in medicine has not thus far been attempted in plant disease management. Nonetheless, as the gut and rhizosphere microbiome are known to share many common traits, there exists a good scope for accomplishing similar studies in agriculture. Based upon the information drawn from all recent works in microbiome studies of gut and rhizosphere, we propose that tailor-made core-microbiome transfer therapy can be a success in agriculture too and it could become a viable strategy for management of plant diseases in future.
On the expected lengths of sequences generated in sorting by replacement selecting

In the replacement-selecting technique of sorting, one is interested in the ratio L<subscrpt>j</subscrpt> of the expected length of the <italic>j</italic>th sequence generated by the technique to the number of memory cells used. Using complex-variable theory, it is shown that L<subscrpt>j</subscrpt> → 2 and that, asymtotically, the average interval between sign changes of L<subscrpt>j</subscrpt> — 2 is 2.6662.
Automatic lecture transcription by exploiting presentation slide information for language model adaptation

The paper addresses language model adaptation for automatic lecture transcription by fully exploiting presentation slide information used in the lecture. As the text in the presentation slides is small in its size and fragmentary in its content, a robust adaptation scheme is addressed by focusing on the keyword and topic information. Several methods are investigated and combined; first, global topic adaptation is conducted based on PLSA (probabilistic latent semantic analysis) using keywords appearing in all slides. Web text is also retrieved to enhance the relevant text. Then, local preference of the keywords are reflected with a cache model by referring to the slide used during each utterance. Experimental evaluations on real lectures show that the proposed method combining the global and local slide information achieves a significant improvement of recognition accuracy, especially in the detection rate of content keywords.
The unreliability of individual physician "report cards" for assessing the costs and quality of care of a chronic disease.

CONTEXT Physician profiling is widely used by many health care systems, but little is known about the reliability of commonly used profiling systems. OBJECTIVES To determine the reliability of a set of physician performance measures for diabetes care, one of the most common conditions in medical practice, and to examine whether physicians could substantially improve their profiles by preferential patient selection. DESIGN AND SETTING Cohort study performed from 1990 to 1993 at 3 geographically and organizationally diverse sites, including a large staff-model health maintenance organization, an urban university teaching clinic, and a group of private-practice physicians in an urban area. PARTICIPANTS A total of 3642 patients with type 2 diabetes cared for by 232 different physicians. MAIN OUTCOME MEASURES Physician profiles for their patients' hospitalization and clinic visit rates, total laboratory resource utilization rate and level of glycemic control by average hemoglobin A1c level with and without detailed case-mix adjustment. RESULTS For profiles based on hospitalization rates, visit rates, laboratory utilization rates, and glycemic control, 4% or less of the overall variance was attributable to differences in physician practice and the reliability of the median physician's case-mix-adjusted profile was never better than 0.40. At this low level of physician effect, a physician would need to have more than 100 patients with diabetes in a panel for profiles to have a reliability of 0.80 or better (while more than 90% of all primary care physicians at the health maintenance organization had fewer than 60 patients with diabetes). For profiles of glycemic control, high outlier physicians could dramatically improve their physician profile simply by pruning from their panel the 1 to 3 patients with the highest hemoglobin A1c levels during the prior year. This advantage from gaming could not be prevented by even detailed case-mix adjustment. CONCLUSIONS Physician "report cards" for diabetes, one of the highest-prevalence conditions in medical practice, were unable to detect reliably true practice differences within the 3 sites studied. Use of individual physician profiles may foster an environment in which physicians can most easily avoid being penalized by avoiding or deselecting patients with high prior cost, poor adherence, or response to treatments.
Current status of non-viral gene therapy for CNS disorders

ABSTRACT Introduction: Viral and non-viral vectors have been used as methods of delivery in gene therapy for many CNS diseases. Currently, viral vectors such as adeno-associated viruses (AAV), retroviruses, lentiviruses, adenoviruses and herpes simplex viruses (HHV) are being used as successful vectors in gene therapy at clinical trial levels. However, many disadvantages have risen from their usage. Non-viral vectors like cationic polymers, cationic lipids, engineered polymers, nanoparticles, and naked DNA offer a much safer option and can therefore be explored for therapeutic purposes. Areas covered: This review discusses different types of viral and non-viral vectors for gene therapy and explores clinical trials for CNS diseases that have used these types of vectors for gene delivery. Highlights include non-viral gene delivery and its challenges, possible strategies to improve transfection, regulatory issues concerning vector usage, and future prospects for clinical applications. Expert opinion: Transfection efficiency of cationic lipids and polymers can be improved through manipulation of molecules used. Efficacy of cationic lipids is dependent on cationic charge, saturation levels, and stability of linkers. Factors determining efficacy of cationic polymers are total charge density, molecular weights, and complexity of molecule. All of the above mentioned parameters must be taken care for efficient gene delivery.
120-GHz-band BPSK modulator and demodulator for 10-Gbit/s data transmission

This paper presents a 120-GHz band binary phase shift keying (BPSK) modulator and demodulator fabricated on microwave monolithic integrated circuits (MMICs) for a 10-Gbit/s wireless link. The direct-conversion modulator consists of a 180° hybrid coupler, gain-control amplifiers, and Wilkinson combiner. The delay demodulator has a 100-ps delay line made of coplanar waveguides and a voltage-controlled phase shifter. The modulator MMIC exhibits a static vector error magnitude of 5%. The modulator and demodulator MMICs were mounted in WR-8 waveguide modules to evaluate the characteristics of 10-Gbit/s transmission. A bit error rate (BER) for 10-Gbit/s pseudorandom binary sequence (PRBS) 27-1 data was 10−12.
Directions for the International Society for Research on Internet Interventions (ISRII)

In 2004, the International Society for Research on Internet Interventions (ISRII) was formed to encourage eHealth researchers to collaborate in their efforts to further the science behind developing, testing, and disseminating Web-based treatment programs. The group held its second meeting (April 2006) to clarify the Society’s direction and identify key issues that need addressing in the field. These issues are identified and examined in the current paper. Given the success of using the Internet to treat a range of medical and mental health problems, and the growing need for better dissemination of health care, Internet interventions will almost certainly play a prominent role in global health. ISRII plans to provide the necessary venue to ensure the science driving this field is strong, enabling researchers to conduct the highest quality research and permitting meaningful conclusions from completed studies.
Familial Aggregation of Atrial Fibrillation: A Study in Danish Twins

Background—Heritability may play a role in nonfamilial atrial fibrillation (AF). We hypothesized that a monozygotic (MZ) twin whose co-twin was diagnosed with AF would have an increased risk of the disease compared with a dizygotic (DZ) twin in the same situation. Methods and Results—A sample of 1137 same-sex twin pairs (356 MZ and 781 DZ pairs) in which one or both members were diagnosed with AF were identified in The Danish Twin Registry. Concordance rates were twice as high for MZ pairs than for DZ pairs regardless of sex (22.0% versus 11.6%, P<0.0001). In a Cox regression of event-free survival times, we compared the time span between occurrences of disease in MZ and DZ twins. The unaffected twin was included when his or her twin-sibling (the index twin) was diagnosed with AF. After adjustment for age at entry, MZ twins had a significantly shorter event-free survival time (hazard ratio, 2.0; 95% CI, 1.3 to 3.0), thereby indicating a genetic component. Using biometric models, we estimated the heritability of AF to be 62% (55% to 68%), due to additive genetics. There were no significant differences across sexes. Conclusions—All the analyses of twin similarities in the present study indicate that genetic factors play a substantial role in the risk of AF for both sexes. The recurrence risk for co-twins (12% to 22%) is clinically relevant and suggests that co-twins of AF-affected twins belong to a high-risk group for AF.