Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined Gold Recovery and Nanoparticle Synthesis in Microbial Systems Using Fractional Factorial Design

Green synthesis of gold nanoparticles (AuNPs) using microorganisms has been generally studied aiming for high-yield production and morphologies appropriated for various applications, such as bioremediation, (bio)sensors, and (bio)catalysis. Numerous approaches showed the individual effect of factors influencing the synthesis of AuNPs with limited analysis of the governing factors enhancing the production and desired quality of the precipitates. This study proposes a fractional-factorial design to investigate the simultaneous influence of seven environmental factors (cell concentration, temperature, anoxic/oxic conditions, pH, gold concentration, electron donor type, and bacterial species) on the recovery yield and synthesis of targeted AuNPs. Various sizes and morphologies of the AuNPs were obtained by varying the environmental factors studied. The factors with significant effects (i.e., 0.2 mM Au and pH 5) were selected according to statistical analysis for optimal removal of 88.2 ± 3.5% of gold and with the production of valuable 50 nm AuNPs, which are known for their enhanced sensitivity. Implications of the cytochrome-C on the bacterial mechanisms and the provision of electron donors via an electrochemical system are further discussed. This study helps develop gold recovery and nanoparticle synthesis methods, focusing on the determining factor(s) for efficient, low-cost, green synthesis of valuable materials.
Global and regional climate in 2001

The average temperature near the surface of the earth in 2001 was approximately 0.42 degC above the 1961± 90 average (Fig. 1(a)). The year was the second warmest in the 141year series; the warmest year so far has been 1998 at 0.55degC above average. Nine of the ten warmest years globally have occurred in the 12 years since 1990. The record warmth in 1998 was increased by the strong El NinÄ o warm event (Parker and Horton 1999), whereas the relative warmth of 2001 occurred despite the mitigating influence of the recent La NinÄ a cool event in the eastern and central tropical Pacific (Parker and Alexander 2001) Weather Vol. 57 September 2002
Why do Social Workers Leave? A Moderated Mediation of Professionalism, Job Satisfaction, and Managerialism

Turnover has been a serious concern to social service organizations. A lack of committed social workers is a risk to organizational performance and service quality. Therefore, it is vital to better understand the leaving process of social work practitioners. The study constructed a moderated mediation model to examine the mediating role of job satisfaction between employees’ professionalism and turnover intention and the moderating role of the perceived level of managerialism in the context of social work organizations. A total of 667 participants from Guangzhou, Shenzhen, and Shanghai in China were recruited to complete the survey. Results presented that job satisfaction plays a full mediation role in the relationship between professionalism and turnover intention. In addition, the positive relationship between professionalism and job satisfaction, as well as the negative relationship between professionalism and turnover intention were moderated by managerialism. The findings enrich knowledge about turnover among social workers in the context of China and inspire to foster professionalism among service workers to improve job satisfaction and alleviate turnover intention and actual turnover as well as to apply management techniques and structures properly to strengthen the effect of professionalism on promoting job satisfaction and on preventing turnover intention.
Robust affine iterative closest point algorithm with bidirectional distance

This study proposes a robust affine iterative closest point (ICP) algorithm based on bidirectional distance for the registration of m -dimensional ( m -D) point sets. Since the affine registration problem can be formulated as a least square (LS) problem by incorporating an affine transformation, this study first analyses the ill-posed problem of the affine registration and turn it into well-posed one by introducing the bidirectional distance into the LS formulation. Then, the corresponding affine ICP algorithm is proposed to solve the well-posed problem. By using the bidirectional distance, the proposed algorithm can directly estimate the affine transformation and converge monotonically to a local minimum from any given initial parameters. To obtain the desired global minimum, good initial parameters can be estimated by independent component analysis (ICA) technique. The proposed approach makes no geometric assumptions on point sets, so it is a general framework for affine registration of m -D point sets. Experimental results demonstrate its robustness and accuracy compared with the current state-of-the-art approaches.
Study on shear dilatancy behaviors of rockfills in large-scale triaxial tests

On the basis of the results of large-scale triaxial tests on typical rockfills for the construction of dams,their shear behaviors under different void ratios or confining pressures including the relationship of(σ1/σ3)-ea and ev-ea,and relationship of dilatancy ratioζ and plastic shear strain esp were analyzed.It was shown that ① For the rockfills with determined particle grading,the conversion between shear dilatancy and shrinkage of the samples depended upon a critical initial void ratio(e0)crit and critical consolidation pressure(σc)crit;② The shear dilatancy ratioζf at the failure of the samples could be a criterion by which whether shear dilantancy appeared or not could be judged.By means of the nonlinear fitting of the results of triaxial tests,the relationship of(σ1/σ3)-e a and the relationship of evp-esp were described by a uniform formulation,and then the equation of stress-dilatancy and the formulation of dilatancy ratioζf at the failure,which depended upon the initial state of the samples,were proposed respectively.So a criterion was established on the formulation of shear dilatancy ratio ζf which depended upon the initial void ratio e0 and confining pressure σc of the samples.
Anomalies in the Optical and Electrical Properties of CrAl Alloys

The frequency dependences of the real and imaginary parts of the complex dielectric constant in the spectral range of 0.069 to 5 eV and the temperature dependences of the resistance of the Cr100–xAlx (x ≦ 32 at % Al) alloy system are investigated. In alloys having 16 to 28 at % of Al, a negative temperature coefficient of resistance, and a minimum metallic conductivity σ(0) < 1000Ω −1 cm−1 a dielectrization of the optical properties is found characterized by strong anomalous concentration and frequency dependences of the dielectric function in the infrared frequency range. From the analysis of the behaviour of the optical σ(ω) and the static σ(0) conductivities it is concluded that the anomalies of optical and electrical properties result from the localization of free carriers near the Fermi level. [Russian Text Ignored]
Optical coherence tomography for dynamic investigation of mammalian reproductive processes

The biological events associated with mammalian reproductive processes are highly dynamic and tightly regulated by molecular, genetic, and biomechanical factors. Implementation of live imaging in reproductive research is vital for the advancement of our understanding of normal reproductive physiology and for improving the management of reproductive disorders. Optical coherence tomography (OCT) is emerging as a promising tool for dynamic volumetric imaging of various reproductive processes in mice and other animal models. In this review, we summarize recent studies employing OCT‐based approaches toward the investigation of reproductive processes in both, males and females. We describe how OCT can be applied to study structural features of the male reproductive system and sperm transport through the male reproductive tract. We review OCT applications for in vitro and dynamic in vivo imaging of the female reproductive system, staging and tracking of oocytes and embryos, and investigations of the oocyte/embryo transport through the oviduct. We describe how the functional OCT approach can be applied to the analysis of cilia dynamics within the male and female reproductive systems. We also discuss the areas of research, where OCT could find potential applications to progress our understanding of normal reproductive physiology and reproductive disorders.
Factors Associated with Self-Report of Type 2 Diabetes Mellitus in Adults Seeking Dental Care in a Developing Country

The aims of the present study were to identify the prevalence and risk indicators of type 2 diabetes mellitus (T2DM) in urban-based Mexican adults seeking care in a university-based triage/intake dental clinic, and to develop a predictive model. A cross-sectional study was conducted on 3354 medical/dental records of adults who sought care at the triage/intake dental clinics of a public university. The dependent variable was self-report of a previous diagnosis of T2DM made by a physician. Several socio-demographic and socioeconomic covariates were included, as well as others related to oral and general health. A multivariate binary logistic regression model was generated. We subsequently calculated well-known statistical measures employed to evaluate discrimination (classification) using an (adjusted) multivariate logistic regression model (goodness-of-fit test). The average age of patients was 42.5 ± 16.1 years old and the majority were female (64.1%). The prevalence of T2DM was 10.7% (95%CI = 9.7–11.8). In the final multivariate model, the variables associated (p < 0.05) with the presence of T2DM were older age (40 to 59 years old, OR = 2.00; 60 to 95 years old, OR = 2.78), having any type of health insurance (OR = 2.33), having high blood pressure (OR = 1.70), being obese (OR = 1.41), and having a functional dentition (OR = 0.68). Although the global fit of the model and the calibration tests were adequate, the sensitivity (0.0%) and positive predictive (0.0%) values were not. The specificity (100%) and negative predictive (89.3%) values, as well as the correctly classified (89.3%) value, were adequate. The area under the ROC curve, close to 0.70, was modest. In conclusion, a prevalence of T2DM of 10.7% in this sample of Mexican adults seeking dental care was similar to national figures. Clinical (blood pressure, BMI and functional dentition), demographic (age), and socioeconomic (health insurance) variables were found to be associated with T2DM. The dental setting could be appropriate for implementing preventive actions focused on identifying and helping to reduce the burden of T2DM in the population.
On resonant differential equations with unbounded non-linearities

We present a method to study asymptotically linear degenerate problems with sublinear unbounded nonlinearities. The method is based on the uniform convergence to zero of projections of nonlinearity increments onto some finite-dimensional spaces. Such convergence was used for the analysis of resonant equations with bounded nonlinearities by many authors [1,2,4,5,7,11–13,17]. The unboundedness of nonlinear terms complicates essentially the analysis of most problems: existence results, approximate methods, systems with parameters, stability, dissipativity, etc. In this paper we present statements on projection convergence for unbounded nonlinearities and apply them to various resonant asymptotically linear problems: existence of forced periodic oscillations and unbounded sequences of such oscillations; existence of unbounded solutions; the sharp analysis of integral equations with the simple degeneration of the linear part (a scalar two-point boundary value problem is considered as an example); existence of nontrivial cycles for higher order autonomous ODEs; Hopf bifurcations at infinity. AMS classification: 34C25, 45M15, 47H11, 47H30 ∗Authors were supported by Grants NN 00-01-00571, 01-01-00146, 01-01-06372, and 00-15-96116 of the Russian Foundation for Basic Researches. The research was partially done while D. I. Rachinskii was visiting the Regensburg University, supported by the Research Fellowship from the Alexander von Humboldt Foundation. E-mails: amk@iitp.ru, direktor@iitp.ru, and rach@iitp.ru.
Gröbner Bases for Ideals of σ-PBW Extensions

In this article, we introduce the σ-PWB extensions and construct the theory of Gröbner bases for the left ideals of them. We prove the Hilbert's basis theorem and the division algorithm for this more general class of Poincaré–Birkhoff–Witt extensions. For the particular case of bijective and quasi-commutative σ-PWB extensions, we implement the Buchberger's algorithm for computing Gröbner bases of left ideals.
Reynolds-averaged Navier–Stokes model predictions of linear instability. I: Buoyancy- and shear-driven flows

Reynolds-averaged Navier–Stokes (RANS) models based on turbulent kinetic energy and dissipation rate or length scale transport equations are commonly used for fully developed turbulence arising from buoyancy, shear, or shocks. It is shown here that RANS models also describe the linear instability phase for buoyancy instabilities (specifically, the Rayleigh–Taylor instability) and shear instabilities (specifically, the Kelvin–Helmholtz instability and stratified shear flow). During the initial phases of the evolution of these models, turbulent diffusion is negligible, the fluctuation energy grows exponentially with negligible coupling to the mean flow, and the model coefficients can be chosen such that the growth rate is equivalent to the physical growth rate of short-wavelength perturbations. The reduced equations obtained by neglecting turbulent diffusion correspond to the unclosed RANS equations under the assumptions of linear theory (i.e., retaining only second-order correlations). The correspondence with linear theory requires interpreting the model length scale as a Lagrangian fluid displacement rather than a quantity derived from the turbulent kinetic energy dissipation rate. The analytical solutions obtained for both the K-ε and K-ℓ models in the absence of diffusion provide insight into the choice of appropriate initial conditions for RANS models, impose various constraints on the model coefficients, and can be used to verify numerical discretizations of the model equations. The analysis also quantifies and addresses issues regarding convergence under grid refinement in the presence of discontinuous mean flows. Paper II [B.M. Johnson and O. Schilling, Reynolds-averaged Navier–Stokes model predictions of linear instability. II: Shock- driven flows, J. Turbul. 12(33) (2011), pp. 1–31] applies the analysis developed herein to shock–turbulence interaction and the Richtmyer–Meshkov instability.
Ten-Year Probabilities of Death Due to Cancer and Cardiovascular Disease among Breast Cancer Patients Diagnosed in North-Eastern Spain

Mortality from cardiovascular disease (CVD), second tumours, and other causes is of clinical interest in the long-term follow-up of breast cancer (BC) patients. Using a cohort of BC patients (N = 6758) from the cancer registries of Girona and Tarragona (north-eastern Spain), we studied the 10-year probabilities of death due to BC, other cancers, and CVD according to stage at diagnosis and hormone receptor (HR) status. Among the non-BC causes of death (N = 720), CVD (N = 218) surpassed other cancers (N = 196). The BC cohort presented a significantly higher risk of death due to endometrial and ovarian cancers than the general population. In Stage I, HR− patients showed a 1.72-fold higher probability of all-cause death and a 6.11-fold higher probability of breast cancer death than HR+ patients. In Stages II–III, the probability of CVD death (range 3.11% to 3.86%) surpassed that of other cancers (range 0.54% to 3.11%). In Stage IV patients, the probability of death from any cancer drove the mortality risk. Promoting screening and preventive measures in BC patients are warranted, since long-term control should encompass early detection of second neoplasms, ruling out the possibility of late recurrence. In patients diagnosed in Stages II–III at an older age, surveillance for preventing late cardiotoxicity is crucial.
Ideal Structure of Multiplier Algebras of Simple C *-algebras With Real Rank Zero

Abstract We give a description of the monoid of Murray-von Neumann equivalence classes of projections for multiplier algebras of a wide class of $\sigma $ -unital simple ${{C}^{*}}$ -algebras $A$ with real rank zero and stable rank one. The lattice of ideals of this monoid, which is known to be crucial for understanding the ideal structure of the multiplier algebra $\mathcal{M}(A)$ , is therefore analyzed. In important cases it is shown that, if $A$ has finite scale then the quotient of $\mathcal{M}(A)$ modulo any closed ideal $I$ that properly contains $A$ has stable rank one. The intricacy of the ideal structure of $\mathcal{M}(A)$ is reflected in the fact that $\mathcal{M}(A)$ can have uncountably many different quotients, each one having uncountably many closed ideals forming a chain with respect to inclusion.
A New Contrastive GAN With Data Augmentation for Surface Defect Recognition Under Limited Data

Surface defect recognition (SDC) is essential in intelligent manufacturing. Deep learning (DL) is a research hotspot in SDC. Limited defective samples are available in most real-world cases, which poses challenges for DL methods. Given such circumstances, generating defective samples by generative adversarial networks (GANs) is applied. However, insufficient samples and high-frequency texture details in defects make GANs very hard to train, yield mode collapse, and poor image quality, which can further impact SDC. To solve these problems, this article proposes a new GAN called contrastive GAN, which can be trained to generate diverse defects with only extremely limited samples. Specifically, a shared data augmentation (SDA) module is proposed for avoiding overfitting. Then, a feature attention matching (FAM) module is proposed to align features for improving the quality of generated images. Finally, a contrastive loss based on hypersphere is employed to constrain GANs to generate images that differ from the traditional transform. Experiments show that the proposed GAN generates defective images with higher quality and lower variance between real defects compared to other GANs. Synthetic images contribute to pretrained DL networks with accuracies of up to 95.00%–99.56% for Northeastern University (NEU) datasets of different sizes and 91.84% for printed circuit board (PCB) cases, which proves the effectiveness of the proposed method.
SARS-CoV-2 variants infectivity prediction and therapeutic peptide design using computational approaches

Abstract The outbreak of severe acute respiratory coronavirus 2 (SARS-CoV-2) has created a public health emergency globally. SARS-CoV-2 enters the human cell through the binding of the spike protein to human angiotensin converting enzyme 2 (ACE2) receptor. Significant changes have been reported in the mutational landscape of SARS-CoV-2 in the receptor binding domain (RBD) of S protein, subsequent to evolution of the pandemic. The present study examines the correlation between the binding affinity of mutated S-proteins and the rate of viral infectivity. For this, the binding affinity of SARS-CoV and variants of SARS-CoV-2 towards ACE2 was computationally determined. Subsequently, the RBD mutations were classified on the basis of the number of strains identified with respect to each mutation and the resulting variation in the binding affinity was computationally examined. The molecular docking studies indicated a significant correlation between the Z-Rank score of mutated S proteins and the rate of infectivity, suitable for predicting SARS-CoV-2 infectivity. Accordingly, a 30-mer peptide was designed and the inhibitory properties were computationally analyzed. Single amino acid-wise mutation was performed subsequently to identify the peptide with the highest binding affinity. Molecular dynamics and free energy calculations were then performed to examine the stability of the peptide-protein complexes. Additionally, selected peptides were synthesized and screened using a colorimetric assay. Together, this study developed a model to predict the rate of infectivity of SARS-CoV-2 variants and propose a potential peptide that can be used as an inhibitor for the viral entry to human. Communicated by Ramaswamy H. Sarma.
Different Tactics of Synthesized Zinc Oxide Nanoparticles, Homeostasis Ions, and Phytohormones as Regulators and Adaptatively Parameters to Alleviate the Adverse Effects of Salinity Stress on Plants

A major abiotic barrier to crop yield and profitability is salt stress, which is most prevalent in arid and semi-arid locations worldwide. Salinity tolerance is complicated and multifaceted, including a variety of mechanisms, and to adapt to salt stress, plants have constructed a network of biological and molecular processes. An expanding field of agricultural research that combines physiological measures with molecular techniques has sought to better understand how plants deploy tolerance to salinity at various levels. As the first line of defense against oxidative damage brought on by salt stress, host plants synthesize and accumulate several osmoprotectants. They (osmoprotectants) and other phytohormones were shown to serve a variety of protective roles for salt stress tolerance. Intrinsic root growth inhibition, which could be a protection mechanism under salty conditions, may be dependent on phytohormone-mediated salt signaling pathways. This article may also make it easier for scientists to determine the precise molecular processes underlying the ZnO-NPs-based salinity tolerance response for some plants. ZnO-NPs are considered to improve plant growth and photosynthetic rates while also positively regulating salt tolerance. When plants are under osmotic stress, their administration to zinc nanoparticles may also affect the activity of antioxidant enzymes. So, ZnO-NPs could be a promising method, side by side with the released osmoprotectants and phytohormones, to relieve salt stress in plants.