Miracle-dz/UniFAR-FTUs huggingface dataset:
Mono-, Bis-, and Tris-Chelate Zn(II) Complexes with Imidazo[1,5-a]pyridine: Luminescence and Structural Dependence

New mono-, bis-, and tris-chelate Zn(II) complexes have been synthesized starting from different Zn(II) salts and employing a fluorescent 1,3-substituted-imidazo[1,5-a]pyridine as a chelating ligand. The products have been characterized by single-crystal X-ray diffraction; mass spectrometry; and vibrational spectroscopy. The optical properties have been investigated to compare the performances of mono-, bis-, and tris-chelate forms. The collected data (in the solid state and in solution) elucidate an important modification of the ligand conformation upon metal coordination; which is responsible for a notable increase in the optical performance. An intense modification of the emission quantum yield along the series in the solid state is observed comparing mono-, bis-, and tris-chelate adducts; independently from the anionic ligand introduced by ionic exchange.
The Promising Role of Self-Compassion in Managing Type 1 Diabetes

Given the demanding daily regimen for type 1 diabetes (T1D) and emphasis on personal responsibility for self-management, people with T1D can experience self-criticism and diabetes distress. How an individual responds to and copes with diabetes-related feedback may influence self-care, health outcomes, and overall well-being. Self-compassion in the context of diabetes has limited but promising research on its ability to alleviate distress in people with T1D. This narrative review captures relevant, existing literature on self-compassion, compassion-based interventions, and T1D and describes four topic areas where diabetes-specific self-compassion and compassion-based interventions may be particularly relevant: (1) diabetes technology use; (2) relationship with eating and body image; (3) social interactions; and (4) healthcare interactions. Compassion-based interventions have the potential to enhance positive coping skills and to alleviate diabetes distress; more research is needed to understand the role of diabetes-specific self-compassion and to develop high-quality evidence-based interventions.
Neutrinoless Double beta Decay in SU(2) x U(1) Theories

It is shown that gauge theories give contributions to neutrinoless double-$\ensuremath{\beta}$ decay [${(\ensuremath{\beta}\ensuremath{\beta})}_{0\ensuremath{\nu}}$] which are not covered by the standard parametrizations. While probably small, their existence raises the question of whether the observation of ${(\ensuremath{\beta}\ensuremath{\beta})}_{0\ensuremath{\nu}}$ implies the existence of a Majorana mass term for the neutrino. For a "natural" gauge theory we argue that this is indeed the case.
Dorsal and ventral fiber tracts of the pOTS in adults and children

• Preprocessing: (a) diffusion tensors were estimated using mrDiffusion (http://white.stanford.edu/software) (b) b0 images were co-registered to the whole-brain anatomy with SPM2. (c) Templates of adult and child DTI data were created by normalizing and averaging the diffusion data (Dougherty et al, 2005). • Fibers were tracked from a large sphere (30mm radius) centered on pOTS ROI. • Fiber tracking using STT (Mori et al., 1999) with 4th order Runge-Kutta correction, step size=1mm, 8 starting point within each voxel. Tract termination criteria were FA 30°. • Fibers were restricted to those with endpoints within a smaller, 8mm radius sphere centered on pOTS ROI. • The resulting fibers were manually pruned and classified by cortical projection zones.
The wavelet finite element method in the dynamic analysis of a functionally graded beam resting on a viscoelastic foundation subjected to a moving load

Abstract Over recent years there has been a growing demand for materials that possess a wide variation of constitutive properties, which may not naturally occur within homogeneous materials. The evolution of composite materials has led to the development of a relatively new class, commonly referred to as functionally graded materials, which consist of two or more materials (often metals and ceramics) with properties varying continuously with respect to spatial coordinates. In this paper, the dynamic response of a functionally graded (FG) beam is analysed using the wavelet finite element method (WFEM). The scaling functions of the Daubechies wavelet and B-spline wavelet on the interval (BSWI) families are employed as interpolating functions for the construction of the wavelet-based FG beam elements; based on Euler Bernoulli beam theory. The FG beam, comprising of steel and alumina, is assumed to vary continuously in the transverse and axial directions according to the power law. The free vibrations behaviour of a FG beam with different material distributions is compared with other approaches from published data to validate and assess the performance of this formulation. A FG beam resting on a viscoelastic foundation is analysed when subjected to a moving point load. The dynamic responses are evaluated using the Newmark time integration method. The effects of the material distribution, velocity of the moving load and damping of the system are discussed based on the numerical examples presented. The results indicate that WFEMs achieve higher levels of accuracy with fewer elements implemented, in comparison to the classical finite element method, in the analysis of the FG beam. Furthermore, the BSWI wavelet-based approach performs better than the Daubechies-based WFEM.
Celsr2‐mediated morphological polarization and functional phenotype of reactive astrocytes in neural repair

Neural repair is highly influenced by reactive astrocytes. Atypical cadherin Celsr2 regulates neuron development and axon regeneration, while its role in glial cells remains unexplored. In this study, we show that Celsr2 is highly expressed in spinal astrocytes of adult mice, and knockout of Celsr2 results in reactive astrocytes with longer protrusions preferentially orientated towards lesion borders in culture scratch assay and injured spinal cord, and elevation of total and active Cdc42 and Rac1 protein in western blots. Inactivation of Celsr2 enhances calcium influx in reactive astrocytes in time‐lapse imaging. Morphological phenotypes of cultured Celsr2−/− astrocytes are rescued by Cdc42 or Rac1 inhibitors. Following spinal cord injury (SCI), Celsr2−/− mice exhibit smaller lesion cavity and glial scar, enhanced fiber regeneration, weaker microglial response, and improved functional recovery than control animals. Similar phenotypes are found in mice with conditional knockout of Celsr2 in astrocytes. In Celsr2−/− mice, astrocyte phenotype is changed and neuroinflammation is alleviated after injury. Inhibiting Cdc42/Rac1 activities compromises astrocyte polarization and the improvement of neural repair and functional recovery in Celsr2−/− mice with SCI. In conclusion, Celsr2 regulates morphological polarization and functional phenotype of reactive astrocytes and inactivating Celsr2 is a potential therapeutic strategy for neural repair.
NUMERICAL SIMULATION OF SHOCKED SOUND WAVES USING COMPACT SCHEME

تاقت شملا ب يرقتل طا قن ثلا ث يذ ة سداسلا ة جردلا ن م طوغضم ما ظن مادخت ساب تابا سحلا ت يرجأ ة ينمزلا تاقت شملل ةب سنلاب ا مأ ، ة يغارفلا تمدخـ تساف ة قيرط (Runge–Kutta) زار ط ن م ٤ ٦ تاذ لقأ نيزخت . مت يددعلا لحلا نع ةجتانلا ةيلاعلا تاددرتلا تاذ ةفئازلا تاجوملا دامخلإو تـ دودح ةفاضإ ةيعانطصا دا مخإ . ة جلاعمل لخد ملا د نع ةع شم ةلصاف دود ح مادخت سا م ت ةلصافلا دود حلا ة جلاعمل و جرخملا د نع ةعشملا ةلصافلا دود حلا كلذ آو ، توصلا ةعرس ن م ل قلأا تاعرسلاب ز يمتملا نايرسلا نايرسلا كلذ ةجلاعمل .
Robust reliable dissipative filtering for Markovian jump nonlinear systems with uncertainties

This paper investigates the problem of robust reliable dissipative filtering for a class of Markovian jump nonlinear systems with uncertainties and time‐varying transition probability matrix described by a polytope. Our main attention is focused on the design of a reliable dissipative filter performance for the filtering error system such that the resulting error system is stochastically stable and strictly (Q,S,R) dissipative. By introducing a novel augmented Lyapunov–Krasovskii functional, a new set of sufficient conditions is obtained for the existence of reliable dissipative filter design in terms of linear matrix inequalities (LMIs). More precisely, a sufficient LMI condition is derived for reliable dissipative filtering that unifies the conditions for filtering with passivity and H∞ performances. Moreover, the filter gains are characterized in terms of solution to a set of linear matrix inequalities. Finally, two numerical examples are provided to demonstrate the effectiveness and potential of the proposed design technique. Copyright © 2016 John Wiley & Sons, Ltd.
1-D Wideband Phased Dielectric Resonator Antenna Array With Improved Radiation Performance Using Characteristic Mode Analysis

A 1-D wideband phased array of the rectangular ring dielectric resonator antenna (RRDRA) is presented for millimeter-wave (mmWave) applications. By using the characteristic mode analysis, it is found that the unwanted higher order mode (HOM) of the RRDRA results in severe gain degradation and high cross-polarization when the array scans. To remedy the problem, each RRDRA is loaded with a pair of silver strips. They can suppress unwanted HOM and enable good scanning performance in a wide frequency range. To demonstrate the idea, a $1\times $ 4 phased RRDRA array was designed, fabricated, and measured for the licensed mmWave bands (24.25–29.5 GHz). Reasonable agreement between the measured and simulated results is observed.
Techniques for Target Recognition Based on Intuitionistic Fuzzy Kernel Matching Pursuit

In order to classify the target samples of diverse importance much more precisely according to the predefined importance of samples in antimissile system,a technique for target recognition based on intuitionistic fuzzy kernel matching pursuit(IFKMP) is proposed.With the help of the advantages of kernel matching pursuit(KMP) and least-squares loss function,intuitionistic fuzzy kernel matching pursuit learning machine(IFKMPLM) is devised and built based on least-squares loss function,which is expanded to any non-squares loss function,following with IFKMPLM based on that build.Ascribing to transforming intuitionistic fuzzy parameter into a renewed form of intuitionistic fuzzy function,the algorithm for ascertaining intuitionistic fuzzy function is also presented,serving for the appointed important target samples possessing much more precise.An extensive experimental comparison among KMP,FKMP,and IFKMP performed on linear and homocentric circle samples,respectively,shows its superiority over others,moreover,the recognition results of the practical target samples prove the high efficiency of the proposed technique.
Identification and Validation of Ferroptosis-Related LncRNAs Signature as a Novel Prognostic Model for Chronic Lymphocytic Leukemia

Background Chronic lymphocytic leukemia (CLL) is a subtype of B-cell malignancy with high heterogeneity. Ferroptosis is a novel cell death induced by iron and lipid peroxidation and exhibits prognostic value in many cancers. Emerging studies on long non-coding RNAs (lncRNAs) and ferroptosis reveal the unique value in tumorigenesis. However, the prognostic value of ferroptosis-related lncRNAs (FRLs) remains unclear in CLL. Aim We aimed to construct a FRLs risk model to predict prognosis and improve prognostic stratification for clinical practice. Methods RNA-sequencing data and clinical characteristics of CLL patients were downloaded from the GEO database. Based on ferroptosis-related genes from FerrDb database, differentially expressed FRLs with prognostic significance were identified and used to generate the risk model. The capability of the risk model was assessed and evaluated. GO and KEGG analyses were performed to confirm biological roles and potential pathways. Results A novel ferroptosis-related lncRNAs prognostic score (FPS) model containing six FRLs (PRKCQ, TRG.AS1, LNC00467, LNC01096, PCAT6 and SBF2.AS1) was identified. Patients in the training and validation cohort were evenly divided into high- and low-risk groups. Our results indicated that patients in the high-risk group had worse survival than those in the low-risk group. Functional enrichment analyses showed that the differently expressed genes (DEGs) between the two groups were enriched in the chemokine signaling pathway, hematopoietic cell lineage, T cell differentiation, TCR pathway and NF-κB pathway. Moreover, significant differences in immune cell infiltration were also observed. Surprisingly, FPS was proved to be an independent prognostic indicator for OS. Conclusion We established and evaluated a novel prognostic risk model with 6 FRLs that could predict prognosis accurately and describe the distinct immune infiltration in CLL.
Semiparametric models and P-splines

P-splines were introduced by Eilers and Marx (1996). We consider semiparametric models where the smooth part of the model can be described by P-splines. A mixed model representation is also considered. We set a simple strategy for the choice of P-spline parameters, ndx, bdeg and pord, and discuss the use of various criteria for smoothing parameter selection. We illustrate our remarks with the analysis of a randomised block design.
Changes in Brain Activation Patterns During Working Memory Tasks in People With Post-COVID Condition and Persistent Neuropsychiatric Symptoms

Background and Objectives Post-COVID condition (PCC) is common and often involves neuropsychiatric symptoms. This study aimed to use blood oxygenation level–dependent fMRI (BOLD-fMRI) to assess whether participants with PCC had abnormal brain activation during working memory (WM) and whether the abnormal brain activation could predict cognitive performance, motor function, or psychiatric symptoms. Methods The participants with PCC had documented coronavirus disease 2019 (COVID-19) at least 6 weeks before enrollment. Healthy control participants had no prior history of COVID-19 and negative tests for severe acute respiratory syndrome coronavirus 2. Participants were assessed using 3 NIH Toolbox (NIHTB) batteries for Cognition (NIHTB-CB), Emotion (NIHTB-EB), and Motor function (NIHTB-MB) and selected tests from the Patient-Reported Outcomes Measurement Information System (PROMIS). Each had BOLD-fMRI at 3T, during WM (N-back) tasks with increasing attentional/WM load. Results One hundred sixty-nine participants were screened; 50 fulfilled the study criteria and had complete and usable data sets for this cross-sectional cohort study. Twenty-nine participants with PCC were diagnosed with COVID-19 242 ± 156 days earlier; they had similar ages (42 ± 12 vs 41 ± 12 years), gender proportion (65% vs 57%), racial/ethnic distribution, handedness, education, and socioeconomic status, as the 21 uninfected healthy controls. Despite the high prevalence of memory (79%) and concentration (93%) complaints, the PCC group had similar performance on the NIHTB-CB as the controls. However, participants with PCC had greater brain activation than the controls across the network (false discovery rate–corrected p = 0.003, Tmax = 4.17), with greater activation in the right superior frontal gyrus (p = 0.009, Cohen d = 0.81, 95% CI 0.15–1.46) but lesser deactivation in the default mode regions (p = 0.001, d = 1.03, 95% CI 0.61–1.99). Compared with controls, participants with PCC also had poorer dexterity and endurance on the NIHTB-MB, higher T scores for negative affect and perceived stress, but lower T scores for psychological well-being on the NIHTB-EB, as well as more pain symptoms and poorer mental and physical health on measures from the PROMIS. Greater brain activation predicted poorer scores on measures that were abnormal on the NIHTB-EB. Discussion Participants with PCC and neuropsychiatric symptoms demonstrated compensatory neural processes with greater usage of alternate brain regions, and reorganized networks, to maintain normal performance during WM tasks. BOLD-fMRI was sensitive for detecting brain abnormalities that correlated with various quantitative neuropsychiatric symptoms.
Pricing and Risk Management of Multi-Assets Financial Instruments to Natural Disasters

ABSTRACT COVID-19 not only led to a significant loss of human lives but also brought indelible economic loss. To transfer the natural disaster risk, a variety of financial instruments written on the environmental phenomena have been developed and issued by financial institutions. The gamma distribution family is characterized by sparsity, heavy tail, and high skewness; thus, it has been widely used to model the data of environmental phenomena. To exploit the versatility of the gamma distribution, Vitiello and Poon propose the pricing model for financial instruments under the general equilibrium risk neutral valuation relationship (RNVR) framework. Though the VP model is capable of pricing financial instruments, their underlying is limited to a single asset. However, the vast majority of firms face various risks and prefer more efficient and cheaper ways to hedge these risks and maintain financial stability. To price multiple-asset financial instruments, this study extends the single-asset VP model to a multi-asset VP model (MVP) under the RNVR framework. Based on the MVP model, this study demonstrates two applications to price basket options and spread options. To manage the pricing of financial instruments that do not have closed-form pricing formulas, this study develops the Monte Carlo simulation method within the MVP model framework. For risk management, this study provides hedge ratios for market practitioners to manage their risk exposures.
Research on Micro-Displacement Measurement Accuracy Enhancement Method Based on Ensemble NV Color Center

This paper builds a corresponding micro-displacement test system based on an ensemble nitrogen-vacancy (NV) color center magnetometer by combining the correlation between a magnetic flux concentrator, a permanent magnet, and micro-displacement. By comparing the measurement results obtained with and without the magnetic flux concentrator, it can be seen that the resolution of the system under the magnetic flux concentrator can reach 25 nm, which is 24 times higher than without the magnetic flux concentrator. The effectiveness of the method is proven. The above results provide a practical reference for high-precision micro-displacement detection based on the diamond ensemble.
A comparison of correlation slotting and sampleand-hold for determination of cross power spectra from LDV measurements

Measurement of turbulent spatial and temporal length scales is an increasingly important aspect of analysis in fluid mechanics. This information is derived either from the cross correlation or the cross spectrum between two measurements. The use of laser Doppler velocimetry (LDV) further complicates the determination of these properties because of the random data acquisition associated with LDV measurements. The calculation of the cross spectrum obtained for two LDV systems using sample-andhold reconstruction procedures is considered. The errors in cross spectrum estimates together with coherence function calculations (i.e. frequency domain cross covariance) are derived for correcting the cross spectrum and, hence, the phase and the coherence are proposed. The results from numerical simulations are shown to produce good results up to and beyond the equivalent Nyquist frequency based on the mean data rate for the sample -and-hold method. Using simulated data with prescribed coherence and phase, a comparison of the results with those obtained from the correlation slotting method is presented and the advantages and limitations of each technique is discussed.
Chasing SUSY Through Parameter Space

In this thesis we explore several physics scenarios based on the Minimal Supersymmetric Standard Model (MSSM) and its extension in terms of Rparity violation. We derive predictions for, and analyse results from, the ongoing experiments at the Large Hadron Collider (LHC). The important role played by statistics and parameter scanning techniques in analysis of large parameter spaces is emphasized. We investigate a class of models where the superpartners of the Higgs and electroweak bosons, the charginos and neutralinos, are nearly degenerate in mass. When R-parity is conserved, this degeneracy can potentially make the lightest chargino long-lived on the timescales of collider physics. However, through a Bayesian analysis of the relevant parameter space, we find that this possibility is disfavoured by current data. In models where R-parity violating interactions are included, supersymmetric particles can decay to final states involving only Standard Model particles. We demonstrate that a small chargino–neutralino mass difference in this case may lead to interesting signals in LHC searches, including resonances of three charged particles. Although the first run of the LHC produced no clear sign of physics beyond the Standard Model, some small, yet intriguing, excesses have been observed in the data. We investigate whether two excesses seen by the CMS and ATLAS experiments in searches for dileptons, jets and missing energy can be interpreted as early hints of supersymmetry. After taking into account the null-results of other LHC searches, we find that the supersymmetric scenarios considered are not viable explanations of the observed excesses.
A Partition Function with the Prime Modulus P > 3

1. Recently Lehner [2]1 developed a convergent series for pi(n) and p2(n), the number of partitions of a positive integer n into summands of the form 51 ? 1 and 51 + 2 respectively. The purpose of this paper is to develop a similar series for p1(n), p2 (n), * (,-1)/2(n), the number of partitions of a positive integer n into summands ofthe form pl ? 1, pl ? 2, pl ? (p 1)72, p being a prime greater than 3. Here, as in the previous paper, we follow the method of Rademacher [5]. We consider the generating functions
Influence of doping on the performance of GaAs/AlGaAs QWIP for long wavelength applications

Effect of doping and other device parameters on inter sub-band transition in the well, responsivity and dark current of GaAs/AlxGa1−xAs quantum well infrared photodetector (QWIP) is investigated using theoretical model. 2X2 Hamiltonian method is used to calculate Eigen energy states in this modelling. Results show that peak absorption, responsivity and spectral broadening width increase nonlinearly with increasing doping concentration in the well. Peak absorption coefficient increases with increase in well width also. Moreover, with increase in mole fraction of Al in AlxGa1−xAs barrier, the inter sub-band absorption is enhanced but, peak wavelength of absorption shifts towards shorter wavelengths. Dark current density depends on both, the doping concentration and applied bias.
Anti-Inflammatory Effect of Izalpinin Derived from Chromolaena leivensis: λ-Carrageenan-Induced Paw Edema and In Silico Model

The flavonoid izalpinin was isolated from the aerial parts of Chromolaena leivensis. Its structural determination was carried out using MS and NMR spectroscopic techniques (1H, 13C). This compound was evaluated for its anti-inflammatory effect in a rat model on λ-carrageenan-induced plantar edema. Paw inflammation was measured at one-hour intervals for seven hours following the administration of λ-carrageenan. Serum creatine kinase (CK) levels were evaluated, obtaining statistically significant results with the treatments at doses of 10 mg/kg (* p < 0.01) and 20 mg/kg (** p < 0.005). The anti-inflammatory effect of the compound was evaluated by using plethysmography, and the results showed significant differences at the three concentrations (10 mg/kg, 20 mg/kg, 40 mg/kg) in the first and third hours after treatment. * p < 0.05; ** p < 0.001; **** p < 0.0001 vs. the negative control group treated with vehicle (DMSO). Lastly, molecular docking analyses reveal that izalpinin has a strong binding affinity with five target proteins involved in the inflammatory process. The analysis using molecular dynamics allowed demonstrating that the ligand–protein complexes present acceptable stability, with RMSD values within the allowed range.