Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of Causal Effects in Latent Strata with an Encouragement for Response

We consider a new approach to deal with non ignorable non response on an outcome variable, in a causal inference framework. Assuming that a binary instrumental variable for non response is available, we provide a likelihood-based approach to identify and estimate heterogeneous causal effects of a binary treatment on specific latent subgroups of units, named principal strata, defined by the non response behavior under each level of the treatment and of the instrument. We show that, within each stratum, non response is ignorable and respondents can be properly compared by treatment status. In order to assess our method and its robustness when the usually invoked assumptions are relaxed or misspecified, we simulate data to resemble a real experiment conducted on a panel survey which compares different methods of reducing panel attrition.
Polymorphisms in TRIB2 and CAPRIN2 Genes Contribute to the Susceptibility to High Myopia-Induced Cataract in Han Chinese Population

Background Myopia has been shown to be associated with many pathological complications including cataracts, and previous evidence supported that high myopia facilitates the formation of cataracts. However, no studies have identified a link between the genetic susceptibility of high myopia-induced cataracts (HMC) and the underlying genetic mechanisms. Our study aimed to determine how the TRIB2 and CAPRIN2 genes correlate to the risk of HMC. Material/Methods In total, we successfully recruited 3162 participants, including 1026 participants with high myopia and cataracts and 2136 controls with high myopia only. For genotyping, 22 tag single nucleotide polymorphisms (SNPs) in TRIB2 and CAPRIN2 genes were chosen. Single marker association analysis and functional effects of significant SNPs were carried out. Results Strong correlation signals were captured for SNP rs890069 (χ2=22.13, P=2.55×10−6) in TRIB2 and SNP rs17739338 (χ2=16.07, P=6.10×10−5) in CAPRIN2. In patients with high myopia, the C allele at SNP rs890069 was strongly linked to cataract risk (OR [95% CI]=1.36 [1.20–1.55]). In patients with high myopia, the T allele at SNP rs17739338 was significantly related to a lower risk of cataract (OR [95% CI]=0.54 [0.40–0.74]). In different types of human tissues, SNPs rs890069 and rs17739338 were found to be significantly correlated to the levels of TRIB2 and CAPRIN2 gene expression. Conclusions Our study indicated that both TRIB2 and CAPRIN2 genes conferred the susceptibility to cataract in patients with high myopia and Chinese Han ancestry. Future research remains necessary for fully understanding the pathogenic mechanisms and genetic characteristics of cataract.
A Generalized Body Force Analogy for the Dynamic Theory of Thermoelasticity

The static and dynamic version of the body force analogy of linear thermoelasticity is extended with respect to the following problem: In a dynamic setting, we present a distribution of imaginary forces, such that the isothermal displacements due to the latter are equal to the difference between the thermal displacements due to a prescribed thermal actuation stress and a certain prescribed displacement field.
Error and stability analysis of boundary methods for elliptic problems with interfaces

In boundary methods, piecewise particular solutions are employed to solve a given elliptic equation within subdomains of some region of interest. A boundary approximation is then obtained by satisfying the interior and exterior boundary conditions in a least squares sense. We examine convergence, derive error norm bounds for approximate solutions and conduct a stability analysis of the associated algebraic problem. The aim of this analysis is to help choosing good partitions of subdomains
Sequence-dependent setup time flexible job shop scheduling problem to minimise total tardiness

This paper studies the problem of scheduling flexible job shops with setup times where the setups are sequence-dependent. The objective is to find the schedule with minimum total tardiness. First, the paper develops a mathematical model in the form of mixed integer linear programming and compares it with the available model in the literature. The proposed model outperforms the available model in terms of both size complexity and computational complexity. Then, an effective metaheuristic algorithm based on iterated local search is proposed and compared with a tabu search and variable neighbourhood search algorithms proposed previously for the same problem. A complete experiment is conducted to evaluate the algorithms for performance. All the results show the superiority of the proposed algorithm against the available ones.
MSH2 and MSH6 in mismatch repair system account for soybean (Glycine max (L.) Merr.) tolerance to cadmium toxicity by determing DNA damage response.

Our aim was to investigate DNA mismatch repair (MMR) genes regulating cadmium tolerance in two soybean cultivars. Cultivars Liaodou 10 (LD10, Cd-sensitive) and Shennong 20 (SN20, Cd-tolerant) seedlings were grown hydroponically on Murashige & Skoog (MS) media containing 0-2.5 mg•L-1 Cd for 4 days. Cd stress induced less random amplified polymorphism DNA (RAPD) polymorphism in LD10 than in SN20 roots, causing G1/S arrest in LD10 and G2/M arrest in SN20 roots. Virus-induced gene silencing (VIGS) of MLH1 in LD10-TRV-MLH1 plantlets showed markedly diminished G1/S arrest, but enhanced root length/area under Cd stress. However, an increase in G1/S arrest and reduction of G2/M arrest occurred in SN20-TRV-MSH2 and SN20-TRV-MSH6 plantlets with decreased root length/area under Cd stress. Taken together, we conclude that low expression of MSH2 and MSH6, involved in the G2/M arrest, results in Cd-induced DNA damage recognition bypassing the MMR system to activate G1/S arrest with the assistance of MLH1. This then leads to repressed root growth in LD10, explaining the inter-varietal difference in Cd tolerance in soybean.
Eco-InfoVis at Work

Currently, there is a broad range of studies dealing with the design and visualization of energy consumption data for the domestic and increasingly for the office context. However, studies addressing the industrial context are quite rare, and due to the diversity of machines, processes, tasks, personal motivations, teams and the specific organizational culture of companies, it is not sufficient to provide only consumption data. For an adequate consideration of these factors, detailed design guidelines and system concepts are currently missing. However, this study shows the potential that a common understanding of consumption data can emerge through suitable visualization to support everyday work and possibilities of data sharing. Therefore, we show exemplarily how a design can be derived from empirically collected requirements and how a system concept can look like that enrich current eco-feedback design research for the industrial context.
Mouse Adapted SARS-CoV-2 (MA10) Viral Infection Induces Neuroinflammation in Standard Laboratory Mice

Increasing evidence suggests that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection impacts neurological function both acutely and chronically, even in the absence of pronounced respiratory distress. Developing clinically relevant laboratory mouse models of the neuropathogenesis of SARS-CoV-2 infection is an important step toward elucidating the underlying mechanisms of SARS-CoV-2-induced neurological dysfunction. Although various transgenic models and viral delivery methods have been used to study the infection potential of SARS-CoV-2 in mice, the use of commonly available laboratory mice would facilitate the study of SARS-CoV-2 neuropathology. Herein we show neuroinflammatory profiles of immunologically intact mice, C57BL/6J and BALB/c, as well as immunodeficient (Rag2−/−) mice, to a mouse-adapted strain of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2 (MA10)). Our findings indicate that brain IL-6 levels are significantly higher in BALB/c male mice infected with SARS-CoV-2 MA10. Additionally, blood-brain barrier integrity, as measured by the vascular tight junction protein claudin-5, was reduced by SARS-CoV-2 MA10 infection in all three strains. Brain glial fibrillary acidic protein (GFAP) mRNA was also elevated in male C57BL/6J infected mice compared with the mock group. Lastly, immune-vascular effects of SARS-CoV-2 (MA10), as measured by H&E scores, demonstrate an increase in perivascular lymphocyte cuffing (PLC) at 30 days post-infection among infected female BALB/c mice with a significant increase in PLC over time only in SARS-CoV-2 MA10) infected mice. Our study is the first to demonstrate that SARS-CoV-2 (MA10) infection induces neuroinflammation in laboratory mice and could be used as a novel model to study SARS-CoV-2-mediated cerebrovascular pathology.
A Growth Algorithm for Neural Network Decision Trees

This paper explores the application of neural network principles to the construction of decision trees from examples. We consider the problem of constructing a tree of perceptrons able to execute a given but arbitrary Boolean function defined on Ni input bits. We apply a sequential (from one tree level to the next) and parallel (for neurons in the same level) learning procedure to add hidden units until the task in hand is performed. At each step, we use a perceptron-type algorithm over a suitable defined input space to minimize a classification error. The internal representations obtained in this way are linearly separable. Preliminary results of this algorithm are presented.
Elastodynamic Features of Nuclear Matter from Macroscopic Model of Giant Magnetic Resonances

The collective model is presented providing a descriptive treatment of the magnetic resonant response of spherical nuclei. The model is based on macroscopic equations assuming elastodynamic behavior of the nuclear Fermi-continuum. Modelling a heavy nucleus by a spherical piece of an elastic continuous substance made up of a degenerate Fermi-system of nucleons, it is argued that nuclear resonant magnetization may be interpreted as the resultant of torsional wavelike vibrations excited inside a nuclear macroparticle. The emphasis is placed on the description of the giant magnetic dipole resonance. This resonance is associated with long wavelength vibrations of the magnetization current induced in the peripheral layer of finite depth, whereas the internal spherical region presumably unaffected by external perturbations is considered as an unperturbed core. The excited collective motion is found to behave like shear non-radial vibrations of a massive peripheral layer against a rotationally invariant core. The Extended Thomas-Fermi method is employed to generate a bulk density profile on the basis of Skyrme forces which is used as an input parameter in calculations of torsional inertia and stiffness of the collective Hamiltonian. Systematic calculations for the energy and total excitation probability of the giant M1 resonance are compared with data obtained both by nuclear resonance fluorescence measurements and by means of backward (e,e′) scattering.
Low-frequency modes of KDP-type crystals and transition mechanism

Abstract The dynamical mechanism of ferroelectric phase transition in KDP-type crystals has been explained by the order-disorder model of locally distorted PO4 tetrahedrons through fitting of the factorized form of dielectric function including the relaxation mode. From this analysis no soft mode appears but the critical slowing down of the relaxation mode occurs toward to the transition temperature.
Investigations on the generation of photonic crystals using two‐photon polymerization (2PP) of inorganic–organic hybrid polymers with ultra‐short laser pulses

Optical devices with micro‐ and nanooptical elements using polymers and, in particular nano‐scaled organic–inorganic hybrid materials such as ORMOCER®s, will be beyond of the next generation of optical components. For the generation of photonic elements, 3D photonic bandgap materials have been proposed as the basis of many devices. In order to create complete 3D photonic bandgaps, materials enabling high refractive index contrast are needed. Combining suitable materials with highly sophisticated processing methods such as two‐photon polymerization (2PP) using femtosecond lasers is a step towards novel photonic elements. The materials and the patterning process will be discussed with respect these applications. In order to demonstrate the potential of the 2PP method, different classes of materials are investigated. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
An evaluation of an array of viruses and fungi in adult Lebanese patients presenting with various dental infections: A cross-sectional study.

INTRODUCTION The role of bacteria in the pathogenesis of periodontitis, pericoronitis, and periapical infections has been well-established. However, the variation in the severity and prognosis of these lesions could suggest a potential role of other microorganisms, such as viruses and fungi. This study aims to evaluate the presence of adenovirus, human papillomavirus-16, Epstein-Barr virus, Candida, and non-Candida fungi in these infections. METHODOLOGY A cross-sectional study including 120 healthy adult patients presenting with dental infections requiring dental extractions were conducted to assess the prevalence and the relative quantity of viruses and fungi in saliva, infected, and healthy tissues using quantitative polymerase chain reaction tests. Samples were collected, and a categorical scale was used for the prevalence and a continuous scale for the relative quantification. Statistical analyses were performed using Chi-square for the prevalence and Wilcoxon rank test for the relative quantification. RESULTS Except for the Epstein-Barr virus and Candida, the presence of viruses and fungi was significantly associated with dental infections. Adenovirus showed an association with pericoronitis, while human papilloma virus-16 exhibited an association with periapical infections. Non-Candida fungi, on the other hand, showed a positive association with all infected tissues and saliva as compared to healthy control lesions except for periapical infections. CONCLUSIONS According to this study, viruses and fungi were found to be prevalent in dental infections. However, their associations with those infections vary depending on the types of viruses or fungi involved and the category of dental infections.
Monoclonal Gammopathies and the Bone Marrow Microenvironment: From Bench to Bedside and Then Back Again

Multiple myeloma (MM) is an incurable hematologic malignancy characterized by a multistep evolutionary pathway, with an initial phase called monoclonal gammopathy of undetermined significance (MGUS), potentially evolving into the symptomatic disease, often preceded by an intermediate phase called “smoldering” MM (sMM). From a biological point of view, genomic alterations (translocations/deletions/mutations) are already present at the MGUS phase, thus rendering their role in disease evolution questionable. On the other hand, we currently know that changes in the bone marrow microenvironment (TME) could play a key role in MM evolution through a progressive shift towards a pro-inflammatory and immunosuppressive shape, which may drive cancer progression as well as clonal plasma cells migration, proliferation, survival, and drug resistance. Along this line, the major advancement in MM patients’ survival has been achieved by the introduction of microenvironment-oriented drugs (including immunomodulatory drugs and monoclonal antibodies). In this review, we summarized the role of the different components of the TME in MM evolution from MGUS as well as potential novel therapeutic targets/opportunities.
On the Null Asymptotic Stabilization of the Two-Dimensional Incompressible Euler Equations in a Simply Connected Domain

We study the asymptotic stabilization of the origin for the two-dimensional (2-D) Euler equation of incompressible inviscid fluid in a bounded domain. We assume that the controls act on an arbitrarily small nonempty open subset of the boundary. We prove the null global asymptotic stabilizability by means of explicit feedback laws if the domain is connected and simply connected.
Amplitude scaling of a static wrinkle at an oil-air interface created by dielectrophoresis forces

Dielectrophoresis forces have been used to create a static periodic wrinkle with a sinusoidal morphology on the surface of a thin layer of 1-decanol oil. The surface deformation occurs when a voltage V is applied between adjacent coplanar strip electrodes in an interdigitated array onto which the oil film is coated. It has been shown experimentally that the peak-to-peak amplitude A of the wrinkle scales according to the functional form A ∝ V2 exp(-αh/p) for a range of oil film thicknesses h (between 15 and 50 μm) and wrinkle pitches p (160, 240, and 320 μm).
Underwater Pollution Tracking Based on Software-Defined Multi-Tier Edge Computing in 6G-Based Underwater Wireless Networks

The forthcoming 6G networks are expected to provide a vision of overlapping aerial-ground-underwater wireless networks. Meanwhile, the rapid development of the Internet of Underwater Things (IoUTs) brings forth many categories of Autonomous Underwater Vehicle (AUV)-assisted Underwater Wireless Networks (UWNs). In this paper, we argue that the AUV-assisted UWNs can be intelligently utilized to track underwater pollution. To perform smart underwater pollution tracking, we propose the paradigm of AUV flock-based networking system and Software-Defined Networking (SDN)-enabled AUV flock Networking System (SDN-AUVNS). We introduce the concept of Mobile Edge Computing (MEC) into the control of SDN-AUVNS and propose the upgrade of the control plane of the SDN-AUVNS to with the multi-tier edge computing ability. By the proposed system architecture, we adopt the artificial potential field theory to construct the network controlling model. And we present the underwater tracking model for SDN-AUVNS, especially for the underwater pollution equipotential line of a particular concentration. Furthermore, to provide accurate path planning for the equipotential line tracking, we utilize the linearizability mechanism to optimize and revise the control input for the SDN-AUVNS. Lastly, we give a fast united control algorithm that can intelligently schedule the SDN-AUVNS to track underwater pollution equipotential lines. In particular, we propose a smart approach with the name of ’Inverse Distance Weighting’ to optimize the detection sample of the SDN-AUVNS. Evaluation results indicate that our proposal is able to track/survey the equipotential lines within a satisfactory error.
Very high mobility two‐dimensional hole gas in Si/GexSi1−x/Ge structures grown by molecular beam epitaxy

Modulation‐doped Si/GexSi1−x/Ge/GexSi1−x structures were fabricated in which a thin Ge layer was employed as the conduction channel for the two‐dimensional hole gas. The strained heterostructure was fabricated on top of a low threading dislocation density, totally relaxed, GexSi1−x buffer layer with a linearly graded Ge concentration profile. The best mobility of the two‐dimensional hole gas is 55 000 cm2/V s at 4.2 K with a concentration‐dependent hole effective mass of ≤0.10m0. The effect of the Ge/GeSi interface roughness on the 2DHG mobility was studied.
The 2dF Galaxy Redshift Survey: the nature of the relative bias between galaxies of different spectral type

We present an analysis of the relative bias between early- and late-type galaxies in the Two-degree Field Galaxy Redshift Survey (2dFGRS) ‐ as define d by the η parameter of Madgwick et al. (2002), which quantifies the spectral type of galaxies in the survey. Our analysis examines the joint counts in cells between early- and late-type galaxies, using approximately cubical cells with sides ranging from 7h 1 Mpc to 42h 1 Mpc. We measure the variance of the counts in cells using the method of Efstathiou et al. (1990), which we find requires a correction for a finite volume effect equivalent t o the integral constraint bias of the autocorrelation function. Using a maximum likelihood technique we fit lognormal models to the one-point density distribution, and develop methods of dealing with biases in the recovered variances resulting from this technique. We use a modifi ed χ 2 technique to determine to what extent the relative bias is consistent with a simple lin ear bias relation; this analysis results in a significant detection of nonlinearity/stochasti city even on large scales. We directly fit deterministic models for the joint density distribution fu nction, f(δE, δL), to the joint counts in cells using a maximum likelihood technique. Our results are consistent with a scale invariant relative bias factor on all scales studied. Linear b ias is ruled out on scales less than l = 28h 1 Mpc. A power-law bias model is a significantly better fit to the data on all but the largest scales studied; the relative goodness of fit of this m odel as compared to that of the linear bias model suggests that any nonlinearity is negligi ble for l & 40h 1 Mpc, consistent with the expectation from theory that the bias should become linear on large scales.
MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS

This paper first provides some useful results on a generalized random coefficient autoregressive model and a generalized hidden Markov model. These results simultaneously imply strict stationarity, existence of higher order moments, geometric ergodicity, and β-mixing with exponential decay rates, which are important properties for statistical inference. As applications, we then provide easy-to-verify sufficient conditions to ensure β-mixing and finite higher order moments for various linear and nonlinear GARCH(1,1), linear and power GARCH(p,q), stochastic volatility, and autoregressive conditional duration models. For many of these models, our sufficient conditions for existence of second moments and exponential β-mixing are also necessary. For several GARCH(1,1) models, our sufficient conditions for existence of higher order moments again coincide with the necessary ones in He and Terasvirta (1999, Journal of Econometrics 92, 173–192).
About our Generation

The text of the chief researcher of the Institute of Philosophy of the Russian Academy of Sciences, who was hired by the Institute of Philosophy at the end of 1980 and was the secretary of the institute committee of the Komsomol in the first half of the 1980s, tells about the fate of the “generation of the eighties” who came to Russian philosophy in the critical era of the new, on this time Gorbachev's, “thaw”. The author recalls the upbeat and inspiring atmosphere of those years, numerous (and previously completely impossible) scientific and creative initiatives of the institute youth of the perestroika and the first post-Soviet years. The author shares his memories of his teachers and mentors, as well as his young friends and colleagues, who now make up the “color” of the Institute of Philosophy.
Machine Learning Developments and Applications in Solid‐Earth Geosciences: Fad or Future?

After decades of low but continuing activity, applications of machine learning (ML) in solid Earth geoscience have exploded in popularity. This special collection provides a snapshot of those applications, which range from data processing to inversion and interpretation, for which ML appears particularly well suited. Inevitably, there are variations in the degree to which these methods have been developed. We hope that the progress seen in some areas will inspire efforts in others. Challenges remain, including the formidable task of how geoscience can keep pace with developments in ML while ensuring the scientific rigor that our field depends on, but with improvements in sensor technology and accelerating rates of data accumulation, the methods of ML seem poised to play an important role for the foreseeable future.