Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental aspects of photodegradable plastics

During the latter half of this century the production of synthetic plastics and fibers has grown so that the total volume of plastics produced world–wide now exceeds that of steel. This paper is concerned with theoretical and experimental studies relating to the environmental consequences of such a rapid shift from a technology based primarily on agriculture, forestry and metallurgy to one based on chemical raw materials such as oil, coal and natural gas. It is shown that plastics and synthetic fibers have the lowest energy costs of all comparable materials and cause less environmental pollution in their production and fabrication. They are easily recycled when not contaminated with other materials and can be manufactured in photo-or biodegradable modifications tailored to highly litter–prone applications. The topics covered include sections on resource costs and renewal, environmental considerations, the technology and role of photodegradable plastics, and experimental studies of the biodegradation of conventional and photodegradable polyethylene, polypropylene and poly(ethylene terephthalate).
Structured redefinition of sound units by merging and splitting for improved speech recognition

The performance of speech recognition systems degrades when the basic sound units used are poorly defined or incon-sistently used. Several attempts have been made to improve dictionaries automatically, either by redefining pronuncia-tions of words in terms of existing sound units, or by redefining the sound units themselves completely. The problem with these approaches is that, while the former is limited by the sound units used, the latter discards all human information that has been incorporated into an expert-designed recognition dictionary. In this paper we propose a new merging-and-splitting algorithm that attempts to redefine the basic sound units used in the dictionary, while maintaining the expert knowledge built into a manually designed dictionary. Sound units from an existing dictionary are merged based on their inherent confusability, as measured by a Monte-Carlo based metric, and subsequently split to maximize the likelihood of the training data. Experiments with the Resource Management database indicate that this approach results in an improvement in recognition accuracy when context-indepen-dent models are used for recognition. When context-dependent models are used, the improvement observed is reduced.
AIS Electronic Library (AISeL)

Strategic IT business alignment deals with the capability of IT to both shape and support business strategy. It can be interpreted as an organizational learning process that combines business and IT knowledge to support business objectives and can positively affect organizational profitability by creating superior strategies that achieve a competitive advantage. These strategies have to be implemented because strategies are only effective when they are translated into actions readily. Therefore, we introduce the concept of operational IT business alignment, reflecting the functional integration at the structural level and representing the link between business and IT structure. Using structural equation modeling and data from 136 banks, we show that operational IT business alignment positively impacts dynamic IT and business capabilities and in turn strategic alignment and firm performance.
Nonlinear Model Predictive Control for Tracking of Underactuated Vessels under Input Constraints

In this paper, a nonlinear model predictive control (NMPC) is presented for position and velocity tracking of underactuated surface vessel with input constraints. A hree-degree-of-freedom (3-DOF) dynamic model is used with only two control variables: namely, surge force and yaw oment. Without frame transformation, a nonlinear, but nvex, opti-mization problem is formulated to minimize the deviation of the vessel states from a time varying reference generated over a fi-nite horizon by a virtual vessel with the same dynamics. A real-time C-code is generated, using ACADO toolkit and qpOASES solver, with multiple shooting technique for discretization andGauss-Newton iteration algorithm, which is computationally efficient, thus enabling real-time implementation of proposed technique. MATLAB simulations is used to assess the validity of the proposed technique.
The Piano Music Companion

We present a system that we call 'The Piano Music Companion' and that is able to follow and understand (at least to some extent) a live piano performance. Within a few seconds this system can identify the piece that is being played, and the position within the piece. It then tracks the progress of the performer over time via a robust score following algorithm. The companion is useful in multiple ways, e.g., it can be used for piece identification, music visualisation, during piano rehearsal and for automatic page turning.
Translating OWL and semantic web rules into prolog: Moving toward description logic programs

Abstract We are researching the interaction between the rule and the ontology layers of the Semantic Web, by comparing two options: 1) using OWL and its rule extension SWRL to develop an integrated ontology/rule language, and 2) layering rules on top of an ontology with RuleML and OWL. Toward this end, we are developing the SWORIER system, which enables efficient automated reasoning on ontologies and rules, by translating all of them into Prolog and adding a set of general rules that properly capture the semantics of OWL. We have also enabled the user to make dynamic changes on the fly, at run time. This work addresses several of the concerns expressed in previous work, such as negation, complementary classes, disjunctive heads, and cardinality, and it discusses alternative approaches for dealing with inconsistencies in the knowledge base. In addition, for efficiency, we implemented techniques called extensionalization, avoiding reanalysis, and code minimization.
Executive Functions in Preschoolers with Adhd, Odd, and Comorbid Adhd-odd: Evidence from Ecological and Performance-based Measures

Executive functioning in 3-year old preschoolers with attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), comorbid ADHD+ODD, and children without any of these conditions (control group) is examined. A community sample including 622 children was diagnosed using a diagnostic interview following DSM-IV criteria, and assessed using the Behavior Rating Inventory of Executive Function Preschool version (BRIEF-P) and the Kiddie-Conners' Continuous Performance Test. The children diagnosed with ADHD showed the poorest executive function (EF) profile in comparison to controls, and were closely followed in this respect by the comorbid ADHD+ODD children. The ADHD and comorbid groups presented similar executive difficulties. The ODD group obtained mean scores statistically equal to those of controls in EF. These findings suggest that, in preschoolers, executive functioning deficits assessed with a performance-based measure or with behavioral descriptions are specific to children with ADHD, in comparison to those with ODD. This study contributes knowledge about executive functions in two prevalent and comorbid disorders in preschool children, ADHD and ODD, knowledge that can help our understanding of specific deficits and the design of specific early intervention initiatives. Ecological and Performance-based measures. Attention deficit-Hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) are common disorders in childhood starting early in life. Among preschoolers, ADHD prevalence ranges between 2% and 3.7%, and that of ODD between 6. press). It has been proposed that the two disorders have a common genetic liability that increases the risk of suffering from both of them (Tuvblad, Zheng, Raine, & Baker, 2009), and which could be associated with dopaminergic and serotoninergic circuits of reward and inhibition. Executive functioning may be a shared deficit in ADHD and ODD (Kochanska, Murray, & Harlan, 2000). Executive functions (EF) are defined as " those self-directed actions needed to choose goals and to create, enact, and sustain actions toward those goals " (Barkley, 2012, p.60). Processes such as inhibition, planning and organizing, working memory, flexibility or emotional control are included in executive functioning. Deficits in executive control may compromise behavioral regulation in emotional and cognitive areas in ADHD and in ODD. ADHD has been conceptualized as a disorder with primary behavioral inhibition deficits that alters the development and effective performance of EF and the self-regulation they permit (Barkley, 2006). Response inhibition, working memory and flexibility assessed by neuropsychological procedures have been consistently associated with ADHD in the preschool period (Pauli-Pott & Becker, 2011) and school-age children Executive Functions in ODD, …
Immunopathogenesis of delayed‐type hypersensitivity

Cell‐mediated immunity is defined as a beneficial host response characterized by an expanded population of specific T cells, which, in the presence of antigens, produce cytokines locally. The activation and recruitment of cells into an area of inflammation is a crucial step in the development of DTH responses. DTH is immunologically a process similar to cell‐mediated immunity, involving T cells and cytokines. CD4 T helper (Th) 1 cells, differentiated from naive Th cells by IL‐12 and IL‐18 produced from macrophages, play a regulatory role in the expression of DTH and activation of macrophages via interferon γ generated by Th1 and natural killer cells. Macrophages accumulate at the site of DTH and become activated through the CD4 Th1 cell‐cytokine‐macrophage axis. However, DTH leads to pathologic responses, such as granulomatous inflammation, calcification, caseation necrosis, and cavity formation. Granulomas usually form as a result of the persistence of a nondegradable product or as the result of DTH responses. DTH is also required for host defense against etiologic agents, such as Mycobacterium tuberculosis. The expression of cell‐mediated immunity/DTH is a double‐edged sword that may contribute to both clearance of the etiologic agent and tissue damage. Microsc. Res. Tech. 53:241–245, 2001. © 2001 Wiley‐Liss, Inc.
Generation of Branched-Chain Fatty Acids through Lipoate-Dependent Metabolism Facilitates Intracellular Growth of Listeria monocytogenes

ABSTRACT The gram-positive bacterial pathogen Listeria monocytogenes has evolved mechanisms to rapidly replicate in the host cytosol, implying efficient utilization of host-derived nutrients. However, the contribution of host nutrient scavenging versus that of bacterial biosynthesis toward rapid intracellular growth remains unclear. Nutrients that contribute to growth of L. monocytogenes include branched-chain fatty acids (BCFAs), amino acids, and other metabolic intermediates generated from acyl-coenzyme A, which is synthesized using lipoylated metabolic enzyme complexes. To characterize which biosynthetic pathways support replication of L. monocytogenes inside the host cytosol, we impaired lipoate-dependent metabolism by disrupting two lipoate ligase genes that are responsible for bacterial protein lipoylation. Interrupting lipoate-dependent metabolism modestly impaired replication in rich broth medium but strongly inhibited growth in defined medium and host cells and impaired the generation of BCFAs. Addition of short BCFAs and amino acids restored growth of the A1A2-deficient (A1A2−) mutant in minimal medium, implying that lipoate-dependent metabolism generates amino acids and BCFAs. BCFAs alone rescued intracellular growth and spread in L2 fibroblasts of the A1A2− mutant. Lipoate-dependent metabolism was also required in vivo, as a wild-type strain robustly outcompeted the lipoylation-deficient mutant in a murine model of listeriosis. The results of this study suggest that lipoate-dependent metabolism contributes to both amino acid and BCFA biosynthesis and that BCFA biosynthesis is preferentially required for intracellular growth of L. monocytogenes.
Detecting Advertising in Radio using Machine Learning

We present an algorithm that can distinguish between advertising and music without understanding it, by extracting key attributes from a radio audio stream. Our method combines advanced filtering of an audio stream with machine learning algorithms to recognise the filtered variables. The result is lightweight enough to run on an embedded processor, and could thus be used to create a device that gives the listener the ability to filter advertising from radio broadcasts.
Vibrotactile Thresholds on the Mastoid and Forehead Position of Deaf Patients Using Radioear B71 and B81

Objectives: The main objective of this study was to measure the vibrotactile thresholds on the mastoid process and forehead positions using patients with bilateral deafness and to compare the results from the two bone conduction vibrators Radioear B71 and B81. Design: There is a possibility that the vibrotactile sensation on the skin makes it difficult to discriminate between sound and vibration. The risk is highest for patients who have bone conduction hearing thresholds in proximity to or worse than their vibrotactile thresholds. All measurements were performed similar to regular bone conduction threshold testing using an audiometer-driven bone conduction vibrator and pulsed warble tones, but the patients were instructed to respond only when feeling vibrations of the bone conduction vibrator instead of when hearing sound. Both the posterior forehead position and the mastoid process position on the temporal bone were tested for comparative reasons. In total, 16 patients participated in the study, 31% females and 69% males of age 29 to 77 years. All subjects were cochlear implant recipients, either uni- or bilaterally implanted. They were selected based on their audiogram data showing unmeasurable unaided hearing. Results: The force level at which the vibrotactile thresholds were reached, increased with frequency from 125 up to 500 Hz, but remained constant for higher frequencies up to 2 kHz. A statistically significant difference was found between the 2 devices at 125 Hz at both the mastoid process and forehead position, where the vibrotactile threshold seem to be more sensitive for B71, possibly due to contribution of distortion components. There was no statistically significant difference in vibrotactile thresholds between the mastoid process and forehead position in absolute values (force level in dB re 1 µN), but in terms of hearing levels (dB HL) there was an average difference of 10 and 9 dB for B71 and B81, respectively. Conclusions: The results indicate that the vibrotactile thresholds can be confounded with bone conduction hearing thresholds measurements up to 500 Hz when using a standard audiometer and in particular when measuring on the forehead position.
Multimodal content-based structure analysis of karaoke music

This paper presents a novel approach for content-based analysis of karaoke music, which utilizes multimodal contents including synchronized lyrics text from the video channel and original singing audio as well as accompaniment audio in the two audio channels. We proposed a novel video text extraction technique to accurately segment the bitmaps of lyrics text from the video frames and track the time of its color changes that are synchronized to the music. A technique that characterizes the original singing voice by analyzing the volume balance between the two audio channels is also proposed. A novel music structure analysis method using lyrics text and audio content is then proposed to precisely identify the verses and choruses of a song, and segment the lyrics into singing phrases. Experimental results based on 20 karaoke music titles of difference languages have shown that our proposed video text extraction technique can detect and segment the lyrics texts with accuracy higher than 90%, and the proposed multimodal approach for music structure analysis method has better performance than the previous methods that are based only on audio content analysis.
A study of fitness inheritance and approximation techniques for multi-objective particle swarm optimization

In this paper, we study the use of fitness inheritance and approximation techniques to reduce the number of fitness evaluations into a PSO-based multi-objective algorithm previously proposed by the authors. Fifteen fitness inheritance techniques and four approximation techniques are applied to a set of four well-known test functions taken from the multi-objective optimization literature. A comparison of the best techniques found against other PSO-based multi-objective approaches is carried out using other test functions. The obtained results show a good performance of the enhancement techniques proposed
Understanding Statin Non-Adherence: Knowing Which Perceptions and Experiences Matter to Different Patients

Background Non-adherence to statins is substantial and is associated with numerous perceptions and experiences. However, time limits in clinical practice constrain in depth explorations of these perceptions and experiences. Objectives To propose and examine a strategy aimed at an efficient assessment of a wide array of perceptions and experiences regarding the efficacy, side effects, and practical problems of statins. Furthermore, to assess associations between this wide array of experiences and perceptions and non-adherence and to examine whether patients' 'perceived self-efficacy' moderated these associations. Methods Patients were recruited through community pharmacies. A wide array of specific patient perceptions and experiences was efficiently assessed using the electronic Tailored Medicine Inventory that allows people to skip irrelevant questions. Adherence was measured through self-report and pharmacy refill data. Results Of the two-hundred twenty-nine patients who participated (mean age 63.9, standard deviation 10.2), 40%-70% doubted the necessity of or lacked knowledge about the efficacy of statins, 20%-35% of the patients were worried about joint and muscle side effects or had experienced these, and 23% had encountered practical problems regarding information about statins, intake of tablets, the package, or the blister. Experiencing more practical problems was associated with increased unintentional non-adherence (Odds ratio 1.54, 95%CI:1.13–2.10, P < 0.01), whereas worrying about side effects was associated with increased intentional non-adherence (Odds ratio 1.90, 95%CI:1.17–3.08, P < 0.01). Higher 'perceived self-efficacy' did not moderate these associations. Conclusions Insight into patients' specific barriers with regard to appropriate statin use may reveal personal reasons for being non-adherent. The Tailored Medicine Inventory is a promising tool to devise individualized intervention strategies aimed at improving adherence by the clinician-patient alliance.
Child labor and the labor supply of other household members: evidence from 1920 America

This paper analyses the effect of child labor on household labor supply using 1920 US Census micro data. The aim of the analysis is to understand who in the household benefits from child labor. In order to identify a source of exogenous variation in child labor I use State-specific child labor laws. I find that a rise in the proportion of working children by household is associated with no variation in parents? labor supply. I also find a strong negative externality among children: as the proportion of working children by household rises, everything else equal, the probability that each child works falls while the probability that he attends school rises. This suggests that parents redistribute entirely the returns from child labor to the children in the household, consistent with a model of household labor supply with fully altruistic parents.
Automatic Assessment of Exercises for Algorithms and Data Structures - a Case Study with TRAKLA2

AbstractThis paper presents the results of the case study introducing TRAKLA2 system inthe course of data structures and algorithms at the University of Turku in 2004. Wecompared students’ learning results with the results of the previous year. The numericalcourse results were clearly better than in 2003 when only pen-and-paper type exercisesin classrooms were used. In addition, a survey was made with over 100 students onthe changes in their attitudes towards web-based learning environments while gettingacquainted with a wholly new system providing them automatic feedback and the optionto resubmit their solutions. Our results show that such an on-line learning environmentconsiderably increases positive attitudes towards web-based learning, and according tostudents’ self-evaluations, the best learning results are achieved by combining traditionalteaching and www-based learning. 1 Introduction Automatic assessment (AA) tools for CS courses are being developed and gaining acceptancemore and more widely at university level education. The survey of the ITiCSE working group“How shall we assess this” in 2003 indicated clearly that the experience of using AA toolscorrelates with a positive attitude towards applying such methods more widely, also whenassessing higher order skills (Carter et al., 2003). The ﬁeld where AA is most widely used isassessing programming exercises (e.g. Higgins et al. (2002); Luck and Joy (1999); Saikkonenet al. (2001); Vihtonen and Ageenko (2002)). Other applications include grading algorithmexercises (Bridgeman et al., 2000; Hyvonen and Malmi, 1993; Korhonen and Malmi, 2000)and analyzing object-oriented designs and ﬂowcharts (Higgins et al., 2002). In this paper, we report the experiences on using the TRAKLA2 system for assessingalgorithm exercises in which students simulate working of algorithms on a conceptual level.TRAKLA2 by Malmi et al. (2004); Korhonen et al. (2003) is a visual algorithm simulationexercise system that has been developed at Helsinki University of Technology (HUT). Studentssolve the exercises using graphical manipulation of conceptual visualizations of data structureson the screen. The system provides automatic formative and summative feedback on theirwork, and allows for resubmitting the solutions.TRAKLA2 exercises were used for the ﬁrst time in the basic data structures and algorithmscourses at HUT in spring 2003. The system was used in parallel with the old TRAKLA systemso that in total 14 TRAKLA2 exercises and 24 TRAKLA exercises were used in two courses
Muscle Hypertrophy in Prepubescent Tennis Players: A Segmentation MRI Study

Purpose To asses if tennis at prepubertal age elicits the hypertrophy of dominant arm muscles. Methods The volume of the muscles of both arms was determined using magnetic resonance imaging (MRI) in 7 male prepubertal tennis players (TP) and 7 non-active control subjects (CG) (mean age 11.0±0.8 years, Tanner 1–2). Results TP had 13% greater total muscle volume in the dominant than in the contralateral arm. The magnitude of inter-arm asymmetry was greater in TP than in CG (13 vs 3%, P<0.001). The dominant arm of TP was 16% greater than the dominant arm of CG (P<0.01), whilst non-dominant arms had similar total muscle volumes in both groups (P = 0.25), after accounting for height as covariate. In TP, dominant deltoid (11%), forearm supinator (55%) and forearm flexors (21%) and extensors (25%) were hypertrophied compared to the contralateral arm (P<0.05). In CG, the dominant supinator muscle was bigger than its contralateral homonimous (63%, P<0.05). Conclusions Tennis at prepubertal age is associated with marked hypertrophy of the dominant arm, leading to a marked level of asymmetry (+13%), much greater than observed in non-active controls (+3%). Therefore, tennis particpation at prepubertal age is associated with increased muscle volumes in dominant compared to the non-dominant arm, likely due to selectively hypertrophy of the loaded muscles.