Miracle-dz/UniFAR-FTUs huggingface dataset:
The Interplay between α-Synuclein and Microglia in α-Synucleinopathies

Synucleinopathies are a set of devastating neurodegenerative diseases that share a pathologic accumulation of the protein α-synuclein (α-syn). This accumulation causes neuronal death resulting in irreversible dementia, deteriorating motor symptoms, and devastating cognitive decline. While the etiology of these conditions remains largely unknown, microglia, the resident immune cells of the central nervous system (CNS), have been consistently implicated in the pathogenesis of synucleinopathies. Microglia are generally believed to be neuroprotective in the early stages of α-syn accumulation and contribute to further neurodegeneration in chronic disease states. While the molecular mechanisms by which microglia achieve this role are still being investigated, here we highlight the major findings to date. In this review, we describe how structural varieties of inherently disordered α-syn result in varied microglial receptor-mediated interactions. We also summarize which microglial receptors enable cellular recognition and uptake of α-syn. Lastly, we review the downstream effects of α-syn processing within microglia, including spread to other brain regions resulting in neuroinflammation and neurodegeneration in chronic disease states. Understanding the mechanism of microglial interactions with α-syn is vital to conceptualizing molecular targets for novel therapeutic interventions. In addition, given the significant diversity in the pathophysiology of synucleinopathies, such molecular interactions are vital in gauging all potential pathways of neurodegeneration in the disease state.
Neural Process for Health Prognostics With Uncertainty Estimations

Gaussian processes (GPs) and neural networks (NNs) are two kinds of function approximation models that are widely used for health prognostics. As an emerging meta-learning method, neural processes (NPs) combine the advantages of GPs and NNs. Similar to GPs, NPs can quickly adapt to new observations and can estimate the uncertainty in their prediction. Similar to NNs, NPs are scalable for complex functions and large datasets. However, NPs do not have the capability to handle the prognostics in the time series prevailing in health prognostics. Inspired by these, an NP-based health prognostic toward prognostic uncertainty is presented. The method is validated by datasets that are sourced from real industrial case. Meanwhile, the proposed method is compared with the state-of-the-art NN- and GP-based health prognostic methods, which are also developed for prognostics with uncertainty estimations. The results show that the proposed method performs the prognostics with superior accuracy and quality.
Degradation of Bio-Based and Biodegradable Plastic and Its Contribution to Soil Organic Carbon Stock

Expanding the use of environmentally friendly materials to protect the environment is one of the key factors in maintaining a sustainable ecological balance. Poly(butylene succinate-co-adipate) (PBSA) is considered among the most promising bio-based and biodegradable plastics for the future with a high number of applications in soil and agriculture. Therefore, the decomposition process of PBSA and its consequences for the carbon stored in soil require careful monitoring. For the first time, the stable isotope technique was applied in the current study to partitioning plastic- and soil-originated C in the CO2 released during 80 days of PBSA decomposition in a Haplic Chernozem soil as dependent on nitrogen availability. The decomposition of the plastic was accompanied by the C loss from soil organic matter (SOM) through priming, which in turn was dependent on added N. Nitrogen facilitated PBSA decomposition and reduced the priming effect during the first 6 weeks of the experiment. During the 80 days of plastic decomposition, 30% and 49% of the released CO2 were PBSA-derived, while the amount of SOM-derived CO2 exceeded the corresponding controls by 100.2 and 132.3% in PBSA-amended soil without and with N fertilization, respectively. Finally, only 4.1% and 5.4% of the PBSA added into the soil was mineralized to CO2, in the treatments without and with N amendment, respectively.
Topics in phonological theory

Dans ce cours nous allons étudier la typologie des processus phonologiques à partir de données de différentes langues. Nous allons établir quelles structures phonologiques sont les plus fréquentes dans les langues du monde, quelles structures et processus sont plus rares et nous allons poursuivre plusieurs modèles théoriques qui proposent des explications typologiques. Nous allons comparer des analyses différentes proposées pour les mêmes données dans une approche générative et non-générative. L'approche générative sera illustrée par des modèles que vous connaissez déjà (règles, représentations autosegmentales) et en plus par la théorie de l'optimalité (Prince & Smolensky 1993 ; McCarthy & Prince 1993) et par d'autres approches s'inscrivant dans le programme de recherche de la phonologie de laboratoire.
Log-Periodogram Regression of Time Series with Long Range Dependence

This paper discusses the estimation of multiple time series models which allow elements of the spectral density matrix to tend to infinity or zero at zero frequency and be unrestricted elsewhere. A form of log-periodogram regression estimate of differencing and scale parameters is proposed, which can provide modest efficiency improvements over a previously proposed method (for which no satisfactory theoretical justification seems previously available) and further improvements in a multivariate context when differencing parameters are a priori equal. Assuming Gaussianity and additional conditions which seem mild, asymptotic normality of the parameter estimates is established.
A Novel Design of Dual-Band Inverse Class-F Shunt-Diode Rectifier for Energy Harvesting

This brief presents a compact and high-efficiency dual-band (DB) rectifier with a novel implementation of a DB inverse class-F (class-F<sup>−1</sup>) harmonic termination incorporated with a DB fundamental matching network for energy harvesting (EH). Specifically, the harmonics of two design frequencies are manipulated properly in the class-F<sup>−1</sup> standard by only five transmission lines (TLINs) with low sensitivity for more precise harmonic termination performance. The DB fundamental matching network is a TLIN-implemented <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-type structure which can transform concurrently two arbitrary complex impedances to the <inline-formula> <tex-math notation="LaTeX">$50\Omega $ </tex-math></inline-formula> standard source. Both two networks are theoretically analyzed and closed-form equations are derived. A prototype using a Schottky diode SMS7621-079LF is fabricated and measured at 2.4 GHz and 3.5 GHz showing that the highest power conversion efficiency (PCE) is achieved at 64.5% for 2.32 GHz and 64.2% for 3.48 GHz with an input power of 5 dBm and load resistor of <inline-formula> <tex-math notation="LaTeX">$680\Omega $ </tex-math></inline-formula> while having a compact dimension of 40mm <inline-formula> <tex-math notation="LaTeX">$\times23$ </tex-math></inline-formula>mm, which indicates advantages of compactness and high PCE, as compared to the existing designs.
Finite Materialisability of Datalog Programs with Metric Temporal Operators

DatalogMTL is an extension of Datalog with metric temporal operators that has recently found applications in stream reasoning and temporal ontology-based data access. In contrast to plain Datalog, where materialisation (a.k.a. forward chaining) naturally terminates in finitely many steps, reaching a fixpoint in DatalogMTL may require infinitely many rounds of rule applications. As a result, existing reasoning systems resort to other approaches, such as constructing large Büchi automata, whose implementations turn out to be highly inefficient in practice. In this paper, we propose and study finitely materialisable DatalogMTL programs, for which forward chaining reasoning is guaranteed to terminate. We consider a data-dependent notion of finite materialisability of a program, where termination is guaranteed for a given dataset, as well as a data-independent notion, where termination is guaranteed regardless of the dataset. We show that, for bounded programs (a natural DatalogMTL fragment for which reasoning is as hard as in the full language), checking data-dependent finite materialisability is ExpSpace-complete in combined complexity and PSpace-complete in data complexity; furthermore, we propose a practical materialisation-based decision procedure that works in doubly exponential time. We show that checking data-independent finite materialisability for bounded progams is computationally easier, namely ExpTime-complete; moreover, we propose sufficient conditions for data-indenpendent finite materialisability that can be efficiently checked. We provide also the complexity landscape of fact entailment for different classes of finitely materialisable programs; surprisingly, we could identify a large class of finitely materialisable programs, called MTL-acyclic programs, for which fact entailment has exactly the same data and combined complexity as in plain Datalog, which makes this fragment especially well suited for big-scale applications.
0.5 V Universal Filter and Quadrature Oscillator Based on Multiple-Input DDTA

This paper presents a universal voltage-mode filter and quadrature oscillator based on low-voltage multiple-input differential difference transconductance amplifier (MI-DDTA). Unlike the previous published DDTAs, that utilize the bulk-driven (BD) multiple-input MOS transistor technique (MI-MOST) in the differential pair of the first stage only, the proposed DDTA, for the first time, utilize the BD MI-MOST in the second stage of the DDTA. This results in capability of providing more arithmetic operations without additional current branches or power dissipation. Hence, simplify the topology of the filter and oscillator applications, by decreasing the count of active blocks. The voltage-mode filter offers high-input and low-output impedances, and both non-inverting and inverting versions of five types of transfer functions, namely low-pass, high-pass, band-pass, band-stop, and all-pass characteristics. The oscillator offers three-phase of quadrature signals, and orthogonal control of the condition and frequency of oscillations. The circuit was designed in Cadence environment using 180 nm CMOS TSMC technology. The voltage supply is 0.5 V and the power consumption of the filter is 472 nW. The simulation results are in accordance with theory and confirm the performance of the proposed circuit.
Miniaturized Wide Stopband Quasi-ellipse Filter Based on Silicon-based IPD Technology

A Miniaturized wide stopband quasi-ellipse filter is presented using Si-based IPD technology. To demonstrate the working mechanism of the proposed BPF, an LC circuit is conceived and analyzed for further study of transmission zeros and poles. The proposed BPF is implemented in the Si-based IPD technology and simulated. A transmission zero is generated above the center frequency due to the cross-coupling, which improves selectivity and out-of-band suppression. It has a center frequency of 2.95GHz with a 3-dB bandwidth of 20.3%, and a minimum insertion loss of 2.08-dB within the passband. The stopband suppression from 3.8GHz to 11GHz is greater than 30-dB. The chip, including the GSG pads, is about 2.33mm×2.36mm.
Fibrosis-Related Gene Profiling in Liver Biopsies of PiZZ α1-Antitrypsin Children with Different Clinical Courses

PiZZ (Glu342Lys) α1-antitrypsin deficiency (AATD) is characterized by intrahepatic AAT polymerization and is a risk factor for liver disease development in children. The majority of PiZZ children are disease free, hence this mutation alone is not sufficient to cause the disease. We investigated Z-AAT polymers and the expression of fibrosis-related genes in liver tissues of PiZZ children with different clinical courses. Liver biopsies obtained during 1979–2010 at the Department of Paediatrics, Karolinska University Hospital, Sweden, were subjected to histological re-evaluation, immunohistochemistry and NanoString-based transcriptome profiling using a panel of 760 fibrosis plus 8 bile acid-related genes. Subjects were divided into three groups based on clinical outcomes: NCH (neonatal cholestasis, favourable outcome, n = 5), NCC (neonatal cholestasis, early cirrhosis and liver transplantation, n = 4), and NNCH (no neonatal cholestasis, favourable outcome, n = 5, six biopsies). Hepatocytes containing Z-AAT polymers were abundant in all groups whereas NCC showed higher expression of genes related to liver fibrosis/cirrhosis and lower expression of genes related to lipid, aldehyde/ketone, and bile acid metabolism. Z-AAT accumulation per se cannot explain the clinical outcomes of PiZZ children; however, changes in the expression of specific genes and pathways involved in lipid, fatty acid, and steroid metabolism appear to reflect the degree of liver injury.
All fourteen Bravais lattices can be fabricated by triple exposure of two-beam interference fringes

A simple method for fabricating three-dimensional photonic crystals with all fourteen Bravais lattice structures and arbitrary lattice constant is proposed. The lattice structure is defined by three primitive translation vectors. The vectors form three triangles on the non-parallel three planes, which shape a tetrahedron, and a united two tetrahedrons forms a parallelepiped, which corresponds to a primitive cell of the lattice. All atoms lie at the vertexes of the parallelepiped where these three planes intersect. This means that all crystal lattices can be described by three sets of periodically aligned planes. The periodically aligned planes, or walls, can easily be fabricated by recording two-beam interference fringes in the recording material with a recording threshold such as a photoresist. Therefore, triple exposure of the twobeam interference fringes can create arbitrary crystal lattice structure. The optical arrangement of the practical interferometer is simplified when the angles between the normal to the recording plane and the three planes are equal. In this arrangement the triple exposure is followed subsequently by simply rotating the recording material around the normal to the recording plane. To create a lattice with arbitrary lattice plane with respect to a recording plane, two axes rotating stage must be used to rotate and tilt the recording plane. This method can create all fourteen Bravais lattices with arbitrary lattice constant while the conventional four-beam interference method creates only a limited number of lattice constants. Mathematical proof and numerical analysis results of this method are also shown.
Machine Learning-Based Respiration Rate and Blood Oxygen Saturation Estimation Using Photoplethysmogram Signals

The continuous monitoring of respiratory rate (RR) and oxygen saturation (SpO2) is crucial for patients with cardiac, pulmonary, and surgical conditions. RR and SpO2 are used to assess the effectiveness of lung medications and ventilator support. In recent studies, the use of a photoplethysmogram (PPG) has been recommended for evaluating RR and SpO2. This research presents a novel method of estimating RR and SpO2 using machine learning models that incorporate PPG signal features. A number of established methods are used to extract meaningful features from PPG. A feature selection approach was used to reduce the computational complexity and the possibility of overfitting. There were 19 models trained for both RR and SpO2 separately, from which the most appropriate regression model was selected. The Gaussian process regression model outperformed all the other models for both RR and SpO2 estimation. The mean absolute error (MAE) for RR was 0.89, while the root-mean-squared error (RMSE) was 1.41. For SpO2, the model had an RMSE of 0.98 and an MAE of 0.57. The proposed system is a state-of-the-art approach for estimating RR and SpO2 reliably from PPG. If RR and SpO2 can be consistently and effectively derived from the PPG signal, patients can monitor their RR and SpO2 at a cheaper cost and with less hassle.
Structure, Resilience and Evolution of the European Air Route Network From 2015 to 2018

In spite of the dynamic nature of air transport, air route networks, i.e. the backbone used to organise aircraft flows, are expected to be mostly static, with small changes occasionally being introduced to improve the efficiency and resilience of the system. By leveraging a large data set of European flights comprising years 2015 to 2018, we analyse its structure and evolution from the perspective of complex networks, with the aim of firstly describing it, and secondly to confirm its static nature. Results depict a highly dynamic system, with major topological changes happening at the end of 2017. Peripheral links are usually more vulnerable, due to the lack of effective reroutings, as well as central regions; additionally, the overall resilience of the network is almost constant throughout time, in spite of an increase in traffic. We further test several hypotheses regarding the design considerations driving such evolution. Beyond specific operational insights, these results highlight the importance of taking into account the evolution of this network in the study of traffic flows.
Restoring Degraded Landscapes through An Integrated Approach Using Geospatial Technologies in the Context of the Humanitarian Crisis in Cox’s Bazar, Bangladesh

The influx of nearly a million refugees from Myanmar's Rakhine state to Cox's Bazar, Bangladesh, in August 2017 put significant pressure on the regional landscape leading to land degradation due to biomass removal to provide shelter and fuel energy and posed critical challenges for both host and displaced population. This article emphasizes geospatial applications at different stages of addressing land degradation in Cox’s Bazar. A wide range of data and methods were used to delineate land tenure, estimate wood fuel demand and supply, assess land degradation, evaluate land restoration suitability, and monitor restoration activities. The quantitative and spatially explicit information from these geospatial assessments integrated with the technical guidelines for sustainable land management and an adaptive management strategy was critical in enabling a collaborative, multi-disciplinary and evidence-based approach to successfully restoring degraded landscapes in a displacement setting.
Management of Polydrug-Resistant Tuberculosis

Background and Objectives: There is a lack of information regarding the effective duration of treatment necessary to prevent the development of acquired resistance when fluoroquinolones (FQ), and/or pyrazinamide (Z) resistance has occurred in patients with polydrug-resistant tuberculosis and isoniazid resistance. The management of these kinds of patients should be carried out in experienced centers according to drug susceptibility test results, clinical status of the patient and the extensity of the disease. Materials and Methods: We evaluated treatment regimens, treatment outcomes, and drug adverse effects in seven patients with polydrug-resistant tuberculosis, including those with Z and/or FQ resistance in a retrospective analysis Results: Regarding the patients with polydrug-resistant tuberculosis in addition to isoniazid (H) resistance, three had Z, two had FQ, and the remaining two had both Z and FQ resistance. In the intensive phase of the treatment, the patients were given at least four drugs according to drug susceptibility tests, and at least three drugs in the continuation phase. The duration of treatment was 9–12 months. Two of the patients were foreign nationals, and could not be followed up with due to returning to their home countries. Regarding the remaining five patients, three of them were terminated as they completed treatment, and two as cured. No recurrence was observed in the first year of the treatment. The most common, and serious drug side effect was seen for amikacin. Conclusions: In patients with polydrug-resistant TB, if Z and/or FQ resistance is detected in addition to H resistance, the treatment of these patients should be conducted on a case-by-case basis, taking into account the patient’s resistance pattern, clinical condition, and disease prognosis. Close monitoring of the side effects will increase the success rate of the treatment.
Absolute length measurement using changeable synthetic wavelength chain

There has been much interest in use of a tunable diode laser for absolute distance interferometry. We report on a novel method? using changeable synthetic wavelength chain (CsWC) to measure absolute length? based on a tunable diode laser. During the measurement, the desired synthetic wavelengths are calculated according to the distance to be measured and the measurement uncertainty. Then by tuning the wavelength of the laser, the desired synthetic wavelength chain is created. In addition, a differential measurement setup, which consists of two dual-beam interferometers, is proposed to test the feasibility of the CSWC method. The experiment results demonstrate that the CSWC method can work effectively. Although under present conditions a measurement uncertainty of only 3 x 10-5 is achieved, it is sufficient to design a differential optical probe.
Robust H 1 Observer-Based Control for a Class of (TS) Fuzzy Descriptor Systems with Time-Varying Delay

In this study, a robust output feedback H 1 learning control strategy for a class of Takagi–Sugeno (TS) fuzzy descriptor systems with time-varying delay and external disturbance is developed. The system is subject to uncertainties and unmeasurable state variables. The appealing attributes of this approach include (i) an appropriate Lyapunov–Krasovskii functional to derive a delay-dependent sufﬁcient condition to guarantee that the system is robustly admissible with H 1 performance and (ii) the design of an observer-based controller such that the closed-loop system exhibits the admissibility as well as the H 1 performance requirement with robustness against uncertainties and time delay. Finally, the validity and applicability of the proposed approach are illuminated by examples.
DOPHOT, A CCD PHOTOMETRY PROGRAM: DESCRIPTION AND TESTS

The design considerations and operation features of DoPHOT, a point spread function fitting (PSF) photometry program, are described. Some relevant details of the PSF fitting are discussed. The quality of the photometry returned by DoPHOT is assessed via reductions of an 'artificial' globular cluster generated from a list with well known magnitudes and colors. Results from comparative tests between DoPHOT and DAOPHOT using this synthetic cluster and real data are also described.
Mixed H 1 and Passive Depth Control for Autonomous Underwater Vehicles with Fuzzy Memorized Sampled-Data Controller

This paper investigates the depth control problem for autonomous underwater vehicles (AUVs) by developing a novel fuzzy memorized sampled-data controller. In particular, the mixed H 1 and passive performance index is considered for disturbances in more practical underwater environments. By means of the Lyapunov–Krasovskii functional method, sufﬁcient criteria are established such that the desired depth can be stabilized while satisfying the prescribed mixed H 1 and passive performance. Then, the desired fuzzy memorized controller is designed in terms of linear matrix inequalities (LMIs). Finally, an illustrative example is provided for demon-strating the feasibility and effectiveness of our derived results.