Miracle-dz/UniFAR-FTUs huggingface dataset:
Passive Control of Linear Systems

We propose a method for designing optimal damping viscosities of dampers in order to calm down vibrations of a structure with given mass and stiffness parameters. Our method is based on the minimization of the trace of the Lyapunov equation in the underlying phase space equipped with the energy norm. We compare our method with other common approaches. AMS subject classification: 70J25, 70Q05
Optimal energy management strategy for hybrid electric vehicles with consideration of battery life

The dissertation offers a systematic analysis on the interdependency between fuel economy and battery capacity degradation in hybrid electric vehicles. Optimal control approaches including Dynamic Programming and Pontryagin’s Minimum Principle are used to develop energy management strategies, which are able to optimally tradeoff fuel consumption and battery aging. Based on the optimal solutions, a real-time implementable battery-aging-conscious Adaptive Equivalent Consumption Management Strategy is proposed, which is able to achieve performance that is comparable to optimal results. In addition, an optimal control based charging strategy for plug-in hybrid electric vehicles and battery electric vehicles is developed, which minimizes battery capacity degradation incurred during charging by optimizing the charging current profile. Combining a generic control-oriented vehicle cabin thermal model with the battery aging model, the benefit of this strategy in terms of decreasing battery aging is significant, when compared with the existing strategies, such as the widely accepted constant current constant voltage (CC-CV) protocol. Thus this dissertation presents a complete set of optimal control solutions related to xEVs with consideration of battery aging.
CMaP – A Collaborative Mapping Platform for Humanitarian Organizations

Within the EO4HumEn+ project (www.zgis.at/humanitarian-services), a collaborative web mapping platform was created, which not only collects the metadata of individual data sets created and enables searches on them, but also provides the functionalities to jointly create maps and other dynamic geospatial visualizations, and share them in collaborative tasks. The data in the web mapping platform can be accessed by read-only permission from all partners involved, and by full access permission for individuals who are entitled to either upload data or perform creative mapping – the so-called editors. A user manual guides editors through the three main steps of uploading, metadata creation and map production, by documenting the naming conventions and metadata requirements, as well as providing essential advice on data handling and mapping. The portal uses standardized formats, like metadata in ISO (International Organization for Standardization), Dublin or FGDC (Federal Geographic Data Committee), or external resources like Open Geospatial Consortium (OGC) Web Map Service (WMS), which offers standardized sharing capabilities via the services already mentioned. The Free and Open Source Software (FOSS) product GeoNode was chosen to implement an entry mask for the EO4HumEn+ data portal.
Cost-Effectiveness of Lung Cancer Screening Using Low-Dose Computed Tomography Based on Start Age and Interval in China: Modeling Study

Background Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death in China. The effectiveness of screening for lung cancer has been reported to reduce lung cancer–specific and overall mortality, although the cost-effectiveness, optimal start age, and screening interval remain unclear. Objective This study aimed to assess the cost-effectiveness of lung cancer screening among heavy smokers in China by incorporating start age and screening interval. Methods A Markov state-transition model was used to assess the cost-effectiveness of a lung cancer screening program in China. The evaluated screening strategies were based on a screening start age of 50-74 years and a screening interval of once or annually. Transition probabilities were obtained from the literature and validated, while cost parameters were derived from databases of local medical insurance bureaus. A societal perspective was adopted. The outputs of the model included costs, quality-adjusted life years (QALYs), and lung cancer–specific mortality, with future costs and outcomes discounted by 5%. A currency exchange rate of 1 CNY=0.1557 USD is applicable. The incremental cost-effectiveness ratio (ICER) was calculated for different screening strategies relative to nonscreening. Results The proposed model suggested that screening led to a gain of 0.001-0.042 QALYs per person as compared with the findings in the nonscreening cohort. Meanwhile, one-time and annual screenings were associated with reductions in lung cancer–related mortality of 0.004%-1.171% and 6.189%-15.819%, respectively. The ICER ranged from 119,974.08 to 614,167.75 CNY per QALY gained relative to nonscreening. Using the World Health Organization threshold of 212,676 CNY per QALY gained, annual screening from a start age of 55 years and one-time screening from the age of 65 years can be considered as cost-effective in China. Deterministic and probabilistic sensitivity analyses were conducted. Conclusions This economic evaluation revealed that a population-based lung cancer screening program in China for heavy smokers using low-dose computed tomography was cost-effective for annual screening of smokers aged 55-74 years and one-time screening of those aged 65-74 years. Moreover, annual lung cancer screening should be promoted in China to realize the benefits of a guideline-recommended screening program.
Serum concentrations of aminoacylase 1 in schizophrenia as a potential biomarker: a case-sibling-control study

Abstract Purpose Aminoacylase 1 (ACY1) catalyzes the hydrolysis reaction during protein degradation. N-acetylamino acids are accumulated in the urine in Aminoacylase 1 deficiency (ACY1D). This study attempts to evaluate the potential of ACY1 as a biomarker for schizophrenia and predict genetic vulnerability in the high-risk population. Material and methods Seventy patients with schizophrenia, twenty-five of which have newly diagnosed, forty-nine unaffected siblings of patients, and fifty-six healthy controls were included in the study. The ELISA method was used to measure serum ACY1. The Positive and Negative Syndrome Scale (PANSS) and The Clinical Global Impression – Severity scale (CGI-S) were used to analyze the severity of the symptoms. Data were analysed statistically by non-parametric tests. Results The finding of the study indicated that the serum levels of ACY1 in patients and siblings were lower compared to healthy controls (p < 0.001 and p = 0.023). There was no statistically significant difference between patients and siblings (p = 0.067). The duration of disease, PANSS total scores, and CGI-S scores did not have a significant association with the ACY1 levels in the patient group (p > 0.005). ACY1 levels among the drug-using patient group and the newly diagnosed patient group showed no notable difference (respectively, p = 0.120 and p = 0.843). Conclusion This study is the first to evaluate the serum ACY1 levels in patients with schizophrenia. The result of the study provides us insight regarding the first hints that ACY1 might be a potential biomarker. Being aware of the molecule will pave the way for further explorations in the field.
Is there a Low Surface Brightness Universe

I have been asked to review some of the arguments for and against the existence of a significant population of Hidden Galaxies, and to concentrate on the distant past and the possible future of this subject, leaving more recent observations to others. In particular I ask how should we correct for selection effects and how are we to resolve contradictory evidence?
Extraordinary large heat current rectification in a hybrid thermal diode

We report the realization of an ultra-efficient low-temperature hybrid heat current rectifier, thermal counterpart of the well-known electric diode. Our design is based on a tunnel junction between two different elements: a normal metal and a superconducting island. Electronic heat current asymmetry in the structure arises from large mismatch between the thermal properties of these two. We demonstrate experimentally temperature differences exceeding $60$ mK between the forward and reverse thermal bias configurations. Our device offers a remarkably large heat rectification ratio up to $\sim 140$ and allows its prompt implementation in true solid-state thermal nanocircuits and general-purpose electronic applications requiring energy harvesting or thermal management and isolation at the nanoscale.
Math 219 Spring 2006

t.5. Characterization of the law of a process by its ﬁnite dimensional distributions. (Kol-mogorov Extension Theorem)6. First and second variation (a.k.a variation and quadratic variation) (see [10, 4]). (a) The Riemann-Stieltjes integral (see [10, 4, 9]) and why it does not work for Brow-nian Motion. (b) With probability one, Brownian Motion has ﬁnite quadratic variation. And hence,it has inﬁnite ﬁrst variation almost surely. (c) In fact, EnhWi(t)o= t. ( hWi(t) is the quadratic variation of the standardBrownian motion W(t). )1
Influence of rotation on the collective properties of nuclei

An attempt is made to give a fairly complete description of the theoretical and experimental investigations into the influence of rotation on the collective properties of nuclei. Attention is centered on the angular-momentum dependence of the correlation properties of the superconducting type, the deformation parameters, and the electrical properties of nuclei. Also considered are the influence of rotation on the volume, the momentum distribution of the nucleons, the spin polarization in the nuclei, and phenomena related to these effects.
Syntax without functional categories

This paper argues against the notion 'functional category' (a kind of word-class) while accepting that individual words may be described as 'function' words or 'content' words. It focuses on the two least controversial examples of functional categories — 'determiner' and 'complementiser' — and argues that neither of these categories is needed; and if this conclusion is correct, there is even less independent support for the more abstract functional categories like 'Inflection' and its subtypes. There is no word-class of 'determiners', because determiners are simply 'transitive' pronouns; nor do 'complementisers' comprise a word-class because the standard complementisers are all different from each other.
Development of the Machine Learning-Based Approach to Access Occupancy Information Through Indoor CO2 Data: for Demand-Driven Building Heating Energy Management

Demand driven building energy management system has gained significant interest in recent years. In order to provide insights for the demand driven building heating energy management at IDE building, TU Delft, this research develops an approach to access real time occupancy information by applying supervised machine learning (ML) classification algorithms on the indoor CO2 data collected from a wireless sensor network (WSN) in the IDE building. Three types of ML classification algorithm including K-nearest neighbors (KNN), support vector machine(SVM) and decision tree (DT) have been applied to build the models, then the models are evaluated and compared with the aim to find the best ones for this case. Data collected from one single occupancy room and one double occupancy room based on the WSN are used to train different classification models, then the models are tested not only on these two rooms (local occupancy modeling), but also on another test room (global occupancy modeling). Results show that, as long as the CO2 sensors are located in the similar distance with occupants, the models trained at one room can be applied for another room with slightly lower accuracy. At single occupancy room, the binary occupancy detection (two classes: 0 or at least 1 occupant) models can reach the accuracy range from 90.6% to 93.8% for local occupancy modeling and from 86% to 89.1% for global occupancy modeling. The SVM (linear) model yields the highest accuracy. At double occupancy room, the binary occupancy detection (two classes: 0 or at least 1 occupant) models can reach the accuracy range from 96.2% to 97.2% for local occupancy modeling and from 89.1% to 91.6% for global occupancy modeling. The KNN (K=10) model yields the highest accuracy. The occupants number estimation (three classes: 0, 1, or 2 occupants) models can reach the accuracy range from 90.2% to 93.7% for local occupancy modeling and from 83.5% to 90.5% for global occupancy modeling. The SVM (linear) mode yields the highest accuracy. It is also found that SVM (linear) model yields the most stable prediction results with less overfitting in the time series, thus it is concluded as the most fit model for both binary occupancy detection and occupants number estimation with the aim to apply for demand-driven heating energy management.
Explicit form for the discrete logarithm over the field ${\rm GF}(p,k)$

For $a$ generator of the multiplicative group of the field $GF(p,k)$, the discrete logarithm of an element $b$ of the field to the base $a$, $b\ne 0$ is that integer $z:1\le z \le p^k -1$, $b=a^z$. The $p$-ary digits which represent $z$ can be described with extremely simple polynomial forms.
Specificity of Immunoglobulin Response to Nontuberculous Mycobacteria Infection in People with Cystic Fibrosis

Lung infections with nontuberculous mycobacteria (NTM), and particularly Mycobacterium abscessus, a pathogen with high antibiotic resistance, are of great concern due to poor clinical outcomes and challenging detection in people with cystic fibrosis and other diseases. Standard detection methods are insensitive and increasingly difficult. ABSTRACT Nontuberculous mycobacteria (NTM) infections are increasingly prevalent in chronic lung diseases, including cystic fibrosis (CF). Mycobacterium abscessus is of particular concern due to relatively greater virulence and intrinsic antimicrobial resistance. Airway culture identification, the standard method for detecting pulmonary infection, is hindered by low sensitivity, long culture times, and reliance on sputum production or lavage. A culture-independent test for detecting NTM infection could complement, or replace, sputum culture, which is becoming more difficult to obtain with reduced sputum production by people with CF (pwCF) on highly effective modulator therapy. We describe an assay for the detection of plasma anti-M. abscessus antibodies of pwCF to antigens from M. abscessus lysates. Anti-M. abscessus IgG and IgA, but not IgM, discriminated with high specificity subjects infected with M. abscessus from those infected by M. avium complex, and from those with distant or no NTM infections. The IgG3 subclass predominated with minor contributions by other subclasses. Both aqueous and organic soluble antigens were recognized by plasma IgG. A validation cohort measuring IgG and IgG3 identified M. abscessus positive subjects, and elevated IgG was sustained over several years. These studies show the benefit of M. abscessus cell lysates to detect plasma IgG of subjects with CF and M. abscessus infections. Subclass analysis suggests that IgG3 is the predominant subtype in these subjects with chronic bacterial infections suggesting a defect in class maturation. Serodiagnosis could be useful to monitor M. abscessus group infections in chronic lung disease as an adjunct or alternative to culture. IMPORTANCE Lung infections with nontuberculous mycobacteria (NTM), and particularly Mycobacterium abscessus, a pathogen with high antibiotic resistance, are of great concern due to poor clinical outcomes and challenging detection in people with cystic fibrosis and other diseases. Standard detection methods are insensitive and increasingly difficult. We describe the measurement of NTM-specific antibodies from plasma to identify subjects infected with M. abscessus. The assay is sensitive and provides information on the immune response to NTM infections. This assay could be used to help identify subjects with NTM pulmonary infections and track disease progression, either alone or in conjunction with other tests.
Analyzing GPS Data for Psychological Research: A Tutorial

The ubiquity of location-data-enabled devices provides novel avenues for psychology researchers to incorporate spatial analytics into their studies. Spatial analytics use global positioning system (GPS) data to assess and understand mobility behavior (e.g., locations visited, movement patterns). In this tutorial, we provide a practical guide to analyzing GPS data in R and introduce researchers to key procedures and resources for conducting spatial analytics. We show readers how to clean GPS data, compute mobility features (e.g., time spent at home, number of unique places visited), and visualize locations and movement patterns. In addition, we discuss the challenges of ensuring participant privacy and interpreting the psychological implications of mobility behaviors. The tutorial is accompanied by an R Markdown script and a simulated GPS data set made available on the OSF.
Food Choice and Prey Selection by Great Cormorants Phalacrocorax carbo in a Shallow Coastal Zone in the Dutch Delta Area: Importance of Local Flatfish Stocks

Coastal breeding Great Cormorants Phalacrocorax carbo foraging in a shallow part of the Dutch North Sea preyed upon abundant marine demersal fish species. In 2010–2012 intensive fish surveys were performed in the Voordelta area and in 2009–2015 Cormorant pellets were sampled in the breeding colony of Breede Water, Voorne, four times per year between March and September. In total 48 fish species were detected in the diet, 38 being marine species. Mainly flatfish were consumed, and European Plaice, Common Dab and Common Sole were the most important prey according to fish mass. Experimental trawling revealed 65 species of fish of which gobies, Herring, Whiting, Sprat, European Plaice and Common Dab were the most abundant. Compared to the trawl data, Cormorants showed a preference for Common Dab and Common Sole and for other solitary bottom fish like sandeels and Shorthorn Sculpin. These species were all common in the area. With respect to uncommon and rare species, no preferential selection was recorded. Densities of flatfish were highest in foraging areas closest to the breeding colony and possible depletion effects were only recorded in Common Dab. This diurnal species was already being preyed upon early in the season. Nocturnal foraging habits in other flatfish species, in combination with burrowing behaviour and rounded body shape are effective anti-predator traits and this was reflected in lower frequencies of these species in the Cormorants' diet. Consumption of freshwater fish by Cormorants at the beginning of the breeding period enabled an early start to breeding, and the increasing availability of flatfish in late spring matched the peak demand of rearing nestlings. The almost exclusive predation on flatfish was probably caused by the near-bottom foraging behaviour of most Cormorants and this habit made the birds feed on other abundant demersal fish species as well, such as Whiting, sandeels, Shorthorn Sculpin, Lesser Weever and dragonet species. And although numerous in the system, this bottom-oriented feeding behaviour of Cormorants therefore resulted in a very limited predation on pelagic fish species. In total we estimate an annual extraction by Cormorants of some 100 tonnes of fish being c. 77,600 kg flatfish and c. 20,700 kg other marine fish. Although with a foraging range partly outside the coastal zone, the extraction of fish by Harbour Seals Phoca vitulina and Grey Seals Halichoerus grypus outnumbered that of Cormorants by a factor of 9. As seals are known flatfish consumers, this suggests that there is competition between mammalian and avian predators on demersal fish stocks in the coastal zone.
Molecular Methods to Study Great Cormorant Feeding Ecology

The feeding ecology of the Great Cormorant Phalacrocorax carbo has been the subject of many studies in which the hard parts of fish, contained in dietary samples such as regurgitated pellets, were identified using morphological characteristics. However, morphological prey identification does not necessarily permit the reliable identification of all fish species due to digestion eroding diagnostic characters and/or morphologically indiscernible hard parts in a range of fish species. Molecular methods have the potential to overcome these obstacles by allowing the detection and identification of minute quantities of prey DNA present in pellets, faeces, and stomach samples. Moreover, DNA of the consumer (i.e. the Cormorant) is also present in dietary samples and can thus be employed for ecological studies too. Here, we present a methodological overview of two molecular approaches commonly used to study trophic interactions, namely diagnostic PCR and next generation sequencing, along with their main advantages and disadvantages. Regarding the use of consumer DNA contained in dietary samples, molecular sexing, i.e. the non-invasive sex determination of the sample-producing bird, is presented. We exemplify the potential of DNA-based methods for future research via a case study on pellets collected at Chiemsee (Germany), which were subjected to molecular and morphological prey identification as well as to molecular sexing. Compared to morphological prey identification, molecular analysis led to a 53% increase in prey species and genera, mainly caused by eight additionally detected cyprinid taxa. For 79% of the pellets, the sex of the pellet-producing Cormorant could be successfully determined via molecular sexing. Our findings highlight the exciting possibilities molecular methods offer for future studies on Cormorant feeding ecology, especially regarding evaluations of prey spectra and the non-invasive assessment of sex-specific differences.
Integration of a Learning Playground into a LMS

There are lot of interactive environments that encourage the practice of computer programming. Despite their usefulness, these systems are naturally disconnected from the schools' educational environments, forcing teachers and students to alternate between tools. This work integrates Agni - a computer programming learning playground - with Moodle Learning Management System (LMS). Unlike the plugins' strategy to link applications to specific LMS, this integration uses a broader approach, through the IMS LTI standard which defines a set of specifications that allows the connection of any LTI-compliant LMS to external tools.
Programming to Learn: Logic and Computation from a Programming Perspective

Programming problems are commonly used as a learning and assessment activity for learning to program. We believe that programming problems can be effective for broader learning goals. In our large-enrolment course, we have designed special programming problems relevant to logic, discrete mathematics, and the theory of computation, and we have used them for formative and summative assessment. In this report, we reflect on our experience. We aim to leverage our students' programming backgrounds by offering a code-based formalism for our mathematical syllabus. We find we can translate many traditional questions into programming problems of a special kind - calling for 'programs' as simple as a single expression, such as a formula or automaton represented in code. A web-based platform enables self-paced learning with rapid contextual corrective feedback, and helps us scale summative assessment to the size of our cohort. We identify several barriers arising with our approach and discuss how we have attempted to negate them. We highlight the potential of programming problems as a digital learning activity even beyond a logic and computation course.