LLukas22/scidocs huggingface dataset:
Nonlinear observer design for two-phase flow heat exchangers of air conditioning systems

This work presents the design of a model-based nonlinear observer of an evaporator (a two-phase flow heat exchanger) for advanced dynamic control of air conditioning and refrigeration systems. A control-oriented, low-order model is derived for the evaporator. Based on sensor measurements of the evaporating temperature, the nonlinear observer can be used to estimate the heat transfer rate and the length of two-phase section that cannot be measured directly. The convergence of the observer is proved using contraction theory. The simulation results and experimental testing also demonstrate the convergence. In air conditioning and refrigeration applications, the nonlinear observer can be utilized to synthesize feedback linearization nonlinear control and provide accurate refrigerant charge inventory estimation and optimization.
Evaluating Bayesian networks' precision for detecting students' learning styles

Students are characterized by different learning styles, focusing on different types of information and processing this information in different ways. One of the desirable characteristics of a Web-based education system is that all the students can learn despite their different learning styles. To achieve this goal we have to detect how students learn: reflecting or acting; steadily or in fits and starts; intuitively or sensitively. In this work, we evaluate Bayesian networks at detecting the learning style of a student in a Web-based education system. The Bayesian network models different aspects of a student behavior while he/she works with this system. Then, it infers his/her learning styles according to the modeled behaviors. The proposed Bayesian model was evaluated in the context of an Artificial Intelligence Web-based course. The results obtained are promising as regards the detection of students learning styles. Different levels of precision were found for the different dimensions or aspects of a learning style. 2005 Elsevier Ltd. All rights reserved.
Minimum-Perimeter Enclosing k-gon

Introduction Let P = p1, . . . , pn be a simple polygon (all polygons are assumed convex throughout this paper). A fundamental problem in geometric optimization is to compute a minimum-area or a minimum-perimeter convex k-gon (denoted QA or Qp, resp.) that encloses P . While efficient algorithms for finding QA are known for more than 20 years [8, 1, 2], the problem of finding Qp has remained open; the problem is posed as open in [3, 6, 7, 9, 12, 14, 5]. 1 Chang and Yap [8] give a comprehensive classification of the incluson/enclosure problems, but do not mention the minimum-perimeter enclosing kgon problem (Enc(Pall, Pk, perimeter), in their terminology) at all. We give the first polynomial-time algorithms for computing Qp. In order to obtain our solution, we prove a structural result about an optimal polygon: Local optimality implies that it is “flush” with P (Lemma 1). As a by-product we obtain an algorithm for finding the minimum-perimeter “envelope” — a convex k-gon with a specified sequence of interior angles. Our proofs are very simple and are based on elementary geometry.2 The exact coordinates of the vertices of Qp are given by the roots of high-degree polynomials. In general, it is impossible to find the coordinates exactly in polynomial time [4]. Thus, given ε > 0 as a part of the input to the problem, we will be satisfied with a (1 + ε)-approximate solution. Finding Qp Our algorithm is based on the following lemma, whose (simple) proof we defer until the next paragraph: Lemma 1. Qp is flush with P , i.e., one of the edges of Qp contains an edge of P . By Lemma 1, we may consider each edge of P as a candidate flush edge with Qp and turn the scene into simple polygon P (Fig. 1). This reduces finding Qp to solving n instances of the problem of finding a shortest (k + 1)-link path in simple polygon P , a problem which can be solved in polynomial time [12]. Thus we have our main result: Theorem 2. Qp can be found in polynomial time.
Sensory and affective pain discrimination after inhalation of essential oils.

OBJECTIVE
The purpose of this investigation was to examine the effects of olfactory absorption of two commonly used therapeutic essential oils on sensory and affective responses to experimentally induced pain.


METHODS
A sex-balanced (13 men and 13 women) randomized crossover design was used to obtain pre- and posttreatment change scores for quantitative sensory ratings of contact heat, pressure, and ischemic pain across separate inhalation treatment conditions using essential oil of lavender, essential oil of rosemary, and distilled water (control). Subjective reports of treatment-related changes in pain intensity and pain unpleasantness were obtained for each condition using a visual analog scale. We interpret our findings with respect to the separate dimensions of sensory and affective processing of pain.


RESULTS
Analyses revealed the absence of changes in quantitative pain sensitivity ratings between conditions. However, retrospectively, subjects' global impression of treatment outcome indicated that both pain intensity and pain unpleasantness were reduced after treatment with lavender and marginally reduced after treatment with rosemary, compared with the control condition.


CONCLUSION
These findings suggest that aromatherapy may not elicit a direct analgesic effect but instead may alter affective appraisal of the experience and consequent retrospective evaluation of treatment-related pain.
Context matters: the impact of unit leadership and empowerment on nurses' organizational commitment.

OBJECTIVE
The aim of this study was to test a multilevel model linking unit-level leader-member exchange quality and structural empowerment to nurses' psychological empowerment and organizational commitment at the individual level of analysis.


BACKGROUND
Few studies have examined the contextual effects of unit leadership on individual nurse outcomes. Workplace empowerment has been related to retention outcomes such as organizational commitment in several studies, but few have studied the impact of specific unit characteristics within which nurses work on these outcomes.


METHODS
We surveyed 3,156 nurses in 217 hospital units to test the multilevel model.


RESULTS
A multilevel path analysis revealed significant individual and contextual effects on nurses' organizational commitment. Both unit-level leader-member exchange quality and structural empowerment had significant direct effects on individual-level psychological empowerment and organizational commitment. Psychological empowerment mediated the relationship between core self-evaluations and organizational commitment at the individual level of analysis.


CONCLUSIONS
The contextual effects of positive supervisor relationships and their influence on empowering working conditions at the unit level and, subsequently, nurses' organizational commitment highlight the importance of leadership for creating conditions that result in a committed nursing workforce.
A Different Approach to Solving the Teacher Shortage Problem

Few educational problems have received more attention in recent times than the failure to ensure that elementary and secondary classrooms are all staffed with qualified teachers. Over the past two decades, dozens of studies, commissions, and national reports have warned of a coming crisis resulting from widespread teacher shortages. This article briefly summarizes a recent study I undertook that used national data to examine the sources of school staffing problems and teacher shortages. This research shows that although these issues are among the most important facing schools, they are also among the least understood. The data also reveal that many currently popular reforms will not solve the staffing problems of schools because they do not address some of their key causes. Disciplines Educational Administration and Supervision | Teacher Education and Professional Development Comments This brief is based on the following Center for the Study of Teaching Policy (CTP) Research Report: Teacher Turnover, Teacher Shortages, and the Organization of Schools. View on the CPRE website. This policy brief is available at ScholarlyCommons: https://repository.upenn.edu/cpre_policybriefs/21
Multifunctional, supramolecular, continuous artificial nacre fibres

Nature has created amazing materials during the process of evolution, inspiring scientists to studiously mimic them. Nacre is of particular interest, and it has been studied for more than half-century for its strong, stiff, and tough attributes resulting from the recognized "brick-and-mortar" (B&M) layered structure comprised of inorganic aragonite platelets and biomacromolecules. The past two decades have witnessed great advances in nacre-mimetic composites, but they are solely limited in films with finite size (centimetre-scale). To realize the adream target of continuous nacre-mimics with perfect structures is still a great challenge unresolved. Here, we present a simple and scalable strategy to produce bio-mimic continuous fibres with B&M structures of alternating graphene sheets and hyperbranched polyglycerol (HPG) binders via wet-spinning assembly technology. The resulting macroscopic supramolecular fibres exhibit excellent mechanical properties comparable or even superior to nacre and bone, and possess fine electrical conductivity and outstanding corrosion-resistance.
Mobile Mental Wellness Training for Stress Management: Feasibility and Design Implications Based on a One-Month Field Study

BACKGROUND
Prevention and management of work-related stress and related mental problems is a great challenge. Mobile applications are a promising way to integrate prevention strategies into the everyday lives of citizens.


OBJECTIVE
The objectives of this study was to study the usage, acceptance, and usefulness of a mobile mental wellness training application among working-age individuals, and to derive preliminary design implications for mobile apps for stress management.


METHODS
Oiva, a mobile app based on acceptance and commitment therapy (ACT), was designed to support active learning of skills related to mental wellness through brief ACT-based exercises in the daily life. A one-month field study with 15 working-age participants was organized to study the usage, acceptance, and usefulness of Oiva. The usage of Oiva was studied based on the usage log files of the application. Changes in wellness were measured by three validated questionnaires on stress, satisfaction with life (SWLS), and psychological flexibility (AAQ-II) at the beginning and at end of the study and by user experience questionnaires after one week's and one month's use. In-depth user experience interviews were conducted after one month's use to study the acceptance and user experiences of Oiva.


RESULTS
Oiva was used actively throughout the study. The average number of usage sessions was 16.8 (SD 2.4) and the total usage time per participant was 3 hours 12 minutes (SD 99 minutes). Significant pre-post improvements were obtained in stress ratings (mean 3.1 SD 0.2 vs mean 2.5 SD 0.1, P=.003) and satisfaction with life scores (mean 23.1 SD 1.3 vs mean 25.9 SD 0.8, P=.02), but not in psychological flexibility. Oiva was perceived easy to use, acceptable, and useful by the participants. A randomized controlled trial is ongoing to evaluate the effectiveness of Oiva on working-age individuals with stress problems.


CONCLUSIONS
A feasibility study of Oiva mobile mental wellness training app showed good acceptability, usefulness, and engagement among the working-age participants, and provided increased understanding on the essential features of mobile apps for stress management. Five design implications were derived based on the qualitative findings: (1) provide exercises for everyday life, (2) find proper place and time for challenging content, (3) focus on self-improvement and learning instead of external rewards, (4) guide gently but do not restrict choice, and (5) provide an easy and flexible tool for self-reflection.
Data Clustering: 50 Years Beyond K-means

Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organisms into a system of ranked taxa: domain, kingdom, phylum, class, etc. Cluster analysis is the formal study of methods and algorithms for grouping, or clustering, objects according to measured or perceived intrinsic characteristics or similarity. Cluster analysis does not use category labels that tag objects with prior identifiers, i.e., class labels. The absence of category information distinguishes data clustering (unsupervised learning) from classification or discriminant analysis (supervised learning). The aim of clustering is to find structure in data and is therefore exploratory in nature. Clustering has a long and rich history in a variety of scientific fields. One of the most popular and simple clustering algorithms, K-means, was first published in 1955. In spite of the fact that K-means was proposed over 50 years ago and thousands of clustering algorithms have been published since then, K-means is still widely used. This speaks to the difficulty in designing a general purpose clustering algorithm and the ill-posed problem of clustering. We provide a brief overview of clustering, summarize well known clustering methods, discuss the major challenges and key issues in designing clustering algorithms, and point out some of the emerging and useful research directions, including semi-supervised clustering, ensemble clustering, simultaneous feature selection during data clustering, and large scale data clustering. 2009 Elsevier B.V. All rights reserved.
Identifying optimal targets of network attack by belief propagation

For a network formed by nodes and undirected links between pairs of nodes, the network optimal attack problem aims at deleting a minimum number of target nodes to break the network down into many small components. This problem is intrinsically related to the feedback vertex set problem that was successfully tackled by spin-glass theory and an associated belief propagation-guided decimation (BPD) algorithm [Zhou, Eur. Phys. J. B 86, 455 (2013)EPJBFY1434-602810.1140/epjb/e2013-40690-1]. In the present work we apply the BPD algorithm (which has approximately linear time complexity) to the network optimal attack problem and demonstrate that it has much better performance than a recently proposed collective information algorithm [Morone and Makse, Nature 524, 65 (2015)NATUAS0028-083610.1038/nature14604] for different types of random networks and real-world network instances. The BPD-guided attack scheme often induces an abrupt collapse of the whole network, which may make it very difficult to defend.
Unintended Pregnancies Observed With Combined Use of the Levonorgestrel Contraceptive Implant and Efavirenz-based Antiretroviral Therapy: A Three-Arm Pharmacokinetic Evaluation Over 48 Weeks

BACKGROUND
Levonorgestrel subdermal implants are preferred contraceptives with an expected failure rate of <1% over 5 years. We assessed the effect of efavirenz- or nevirapine-based antiretroviral therapy (ART) coadministration on levonorgestrel pharmacokinetics.


METHODS
This nonrandomized, parallel group, pharmacokinetic evaluation was conducted in three groups of human immunodeficiency virus-infected Ugandan women: ART-naive (n = 17), efavirenz-based ART (n = 20), and nevirapine-based ART (n = 20). Levonorgestrel implants were inserted at baseline in all women. Blood was collected at 1, 4, 12, 24, 36, and 48 weeks. The primary endpoint was week 24 levonorgestrel concentrations, compared between the ART-naive group and each ART group by geometric mean ratio (GMR) with 90% confidence interval (CI). Secondary endpoints included week 48 levonorgestrel concentrations and unintended pregnancies.


RESULTS
Week 24 geometric mean levonorgestrel concentrations were 528, 280, and 710 pg/mL in the ART-naive, efavirenz, and nevirapine groups, respectively (efavirenz: ART-naive GMR, 0.53; 90% CI, .50, .55 and nevirapine: ART-naive GMR, 1.35; 90% CI, 1.29, 1.43). Week 48 levonorgestrel concentrations were 580, 247, and 664 pg/mL in the ART-naive, efavirenz, and nevirapine groups, respectively (efavirenz: ART-naive GMR, 0.43; 90% CI, .42, .44 and nevirapine: ART-naive GMR, 1.14; 90% CI, 1.14, 1.16). Three pregnancies (3/20, 15%) occurred in the efavirenz group between weeks 36 and 48. No pregnancies occurred in the ART-naive or nevirapine groups.


CONCLUSIONS
Within 1 year of combined use, levonorgestrel exposure was markedly reduced in participants who received efavirenz-based ART, accompanied by contraceptive failures. In contrast, nevirapine-based ART did not adversely affect levonorgestrel exposure or efficacy.


CLINICAL TRIALS REGISTRATION
NCT01789879.
The sensitivity and specificity of optical coherence tomography for the assisted diagnosis of nonpigmented basal cell carcinoma: an observational study.

BACKGROUND
The diagnostic criteria for basal cell carcinoma (BCC) using optical coherence tomography (OCT) have been described previously, but the clinical value of these findings remains unknown.


OBJECTIVES
To investigate the diagnostic value of OCT for BCC in a typical clinical setting. The primary efficacy end point was a diagnosis of BCC for each lesion. Secondary end points were the diagnosis of other possible conditions.


METHODS
This was an observational, prospective, multicentre study in which consecutive patients with nonpigmented pink lesions suspicious for BCC underwent clinical assessment, dermoscopy and OCT, with the diagnosis recorded at each stage. Once all diagnoses had been recorded, the histological results were disclosed. In total 164 patients with 256 lesions were recruited. Histology was missing for 21 lesions, leaving 235 lesions in 155 patients for analysis.


RESULTS
Sixty per cent of lesions (141 of 235) were identified as BCC by histology. A slight increase of sensitivity was noted following OCT, which did not reach statistical significance. The specificity increased significantly from 28·6% by clinical assessment to 54·3% using dermoscopy and to 75·3% with the addition of OCT (P < 0·001). The positive predictive value for the diagnosis of BCC using OCT was 85·2% [95% confidence interval (CI) 78·6-90·4], and the negative predictive value was 92·1% (95% CI 83·6-97·0). The accuracy of diagnosis for all lesions increased from 65·8% with clinical evaluation to 76·2% following additional dermoscopy and to 87·4% with the addition of OCT.


CONCLUSIONS
OCT significantly improved the diagnostic specificity for BCC compared with clinical assessment and dermoscopy alone.
Infectious bursal disease virus structural protein VP 2 expressed by a fowlpox virus recombinant confers protection against disease in chickens

Two fowlpox virus recombinants were constructed which expressed the host-protective antigen, VP 2, of infectious bursal disease virus (IBDV). Recombinant FPV-VP 2.4.3 contained the gene for the VP 2-VP 4-VP 3 polyprotein under the control of the vaccinia virus late promoter P.L 11 inserted within the thymidine kinase (TK) gene of FPV. In infected chicken embryo skin (CES) cells VP 2 and VP 3 proteins were correctly processed from the polyprotein precursor molecule. Recombinant FPV-VP 2 contained only the VP 2 encoding region under the control of the fowlpox early/late promoter P.E/L inserted immediately downstream of theTK gene. The expression level of VP 2 from FPV-VP 2 was approximately 5 times higher than from FPV-VP 2.4.3. Wing web inoculation of birds resulted in the development of typical fowlpox lesions and the development of antibodies to FPV with either of the recombinants, but only birds vaccinated with FPV-VP 2 developed antibodies to IBDV. When challenged with IBDV (strain 002-73), a significant level of protection was provided by FPV-VP 2 vaccination, although the level was lower than the protection provided by an oil adjuvanted inactivated whole IBDV vaccine. Birds vaccinated with FPV-VP 2.4.3 were not protected from infection as assessed by ELISA for the presence of IBD virus in bursae.
Of motifs and goals: mining trajectory data

In response to the increasing volume of trajectory data obtained, e.g., from tracking athletes, animals, or meteorological phenomena, we present a new space-efficient algorithm for the analysis of trajectory data. The algorithm combines techniques from computational geometry, data mining, and string processing and offers a modular design that allows for a user-guided exploration of trajectory data incorporating domain-specific constraints and objectives.
Constraint-handling in nature-inspired numerical optimization: Past, present and future

In their original versions, nature-inspired search algorithms such as evolutionary algorithms and those based on swarm intelligence, lack a mechanism to deal with the constraints of a numerical optimization problem. Nowadays, however, there exists a considerable amount of research devoted to design techniques for handling constraints within a nature-inspired algorithm. This paper presents an analysis of the most relevant types of constraint-handling techniques that have been adopted with nature-inspired algorithms. From them, the most popular approaches are analyzed in more detail. For each of them, some representative instantiations are further discussed. In the last part of the paper, some of the future trends in the area, which have been only scarcely explored, are briefly discussed and then the conclusions of this paper are presented. © 2011 Elsevier B.V. All rights reserved.
A pragmatic randomized controlled study of the effectiveness and cost consequences of exercise therapy in hip osteoarthritis.

OBJECTIVE
To evaluate the short- and long-term effectiveness of exercise training in relation to pain, function and direct costs to health care systems attributable to hip osteoarthritis.


DESIGN
Prospective, two-year randomized controlled trial.


SETTING
An outpatient primary health care setting.


SUBJECTS
One hundred and twenty men and women aged from 55 to 80, with radiologically diagnosed hip osteoarthritis with associated clinical symptoms.


INTERVENTIONS
The combined exercise and general practitioner (GP) care group received 12 supervised (once per week) exercise sessions at the baseline and four additional booster sessions one year later. Both groups received standard GP care.


MAIN MEASURES
The WOMAC Osteoarthritis Index, physical functioning score of RAND-36 (SF-36), the use and health care system costs of doctor visits and physiotherapy associated with hip osteoarthritis, number of total hip replacements, the use of analgesic and non-steroidal anti-inflammatory drugs (NSAIDs), performance-based outcome scores and body mass index (BMI).


RESULTS
There were no differences between the groups with respect to WOMAC hip pain, physical functioning score of RAND-36, performance-based outcome scores or BMI. The effect of the exercise intervention on WOMAC function was statistically significant at 6 months (mean = -7.5; 95% confidence interval (CI) -13.9 to -1.0; P = 0.02) and 18 months (mean = -7.9; 95% CI -15.3 to -0.4; P = 0.04). There were no statistically significant differences in the total health care system costs between the groups.


CONCLUSION
The mostly home-based exercise training programme provided in this study did not result in reduced hip pain over the two-year follow-up period.