Miracle-dz/UniFAR-FTUs huggingface dataset:
Copper (I) or (II) Replacement of the Structural Zinc Ion in the Prokaryotic Zinc Finger Ros Does Not Result in a Functional Domain

A strict interplay is known to involve copper and zinc in many cellular processes. For this reason, the results of copper’s interaction with zinc binding proteins are of great interest. For instance, copper interferences with the DNA-binding activity of zinc finger proteins are associated with the development of a variety of diseases. The biological impact of copper depends on the chemical properties of its two common oxidation states (Cu(I) and Cu(II)). In this framework, following the attention addressed to unveil the effect of metal ion replacement in zinc fingers and in zinc-containing proteins, we explore the effects of the Zn(II) to Cu(I) or Cu(II) replacement in the prokaryotic zinc finger domain. The prokaryotic zinc finger protein Ros, involved in the horizontal transfer of genes from A. tumefaciens to a host plant infected by it, belongs to a family of proteins, namely Ros/MucR, whose members have been recognized in different bacteria symbionts and pathogens of mammals and plants. Interestingly, the amino acids of the coordination sphere are poorly conserved in most of these proteins, although their sequence identity can be very high. In fact, some members of this family of proteins do not bind zinc or any other metal, but assume a 3D structure similar to that of Ros with the residues replacing the zinc ligands, forming a network of hydrogen bonds and hydrophobic interactions that surrogates the Zn-coordinating role. These peculiar features of the Ros ZF domain prompted us to study the metal ion replacement with ions that have different electronic configuration and ionic radius. The protein was intensely studied as a perfectly suited model of a metal-binding protein to study the effects of the metal ion replacement; it appeared to tolerate the Zn to Cd substitution, but not the replacement of the wildtype metal by Ni(II), Pb(II) and Hg(II). The structural characterization reported here gives a high-resolution description of the interaction of copper with Ros, demonstrating that copper, in both oxidation states, binds the protein, but the replacement does not give rise to a functional domain.
Water Color Identification System for Monitoring Aquaculture Farms

This study presents a vision-based water color identification system designed for monitoring aquaculture ponds. The algorithm proposed in this system can identify water color, which is an important factor in aquaculture farming management. To address the effect of outdoor lighting conditions on the proposed system, a color correction method using a color checkerboard was introduced. Several candidates for water-only image patches were extracted by performing image segmentation and fuzzy inferencing. Finally, a deep learning-based model was employed to identify the color of these patches and then find the representative color of the water. Experiments at different aquaculture sites verified the effectiveness of the proposed system and its algorithm. The color identification accuracy exceeded 96% for the test data.
The Risk Factors and Mechanisms of Azole Resistance of Candida tropicalis Blood Isolates in Thailand: A Retrospective Cohort Study

In recent decades, an epidemiological shift has been observed from Candida infections to non-albicans species and resistance to azoles. We investigated the associated factors and molecular mechanisms of azole-resistant blood isolates of C. tropicalis. Full-length sequencing of the ERG11 gene and quantitative real-time RT-PCR for the ERG11, MDR1, and CDR1 genes were performed. Male sex (odds ratio, 0.38), leukemia (odds ratio 3.15), and recent administration of azole (odds ratio 10.56) were associated with isolates resistant to azole. ERG11 mutations were found in 83% of resistant isolates, with A395T as the most common mutation (53%). There were no statistically significant differences in the expression of the ERG11, MDR1, and CDR1 genes between the groups resistant and susceptible to azole. The prevalence of azole-resistant isolates was higher than the usage of antifungal drugs, suggesting the possibility of environmental transmission in the healthcare setting. The unknown mechanism of the other 17% of the resistant isolates remains to be further investigated.
Corporate Social Responsibility's (CSR) Impact on Financial Performance: Moderating Effects of Earnings Management and Leverage

Research aims: This research attempts to test the impact of CSR on financial performance, with earnings management and leverage acting as moderating factors.Design/Methodology/Approach: The manufacturing companies listed on the Indonesia Stock Exchange (IDX) from 2015 to 2019 served as the study object. Purposive sampling was utilized in sample selection, yielding 228 samples. Multiple linear regression and moderated regression analysis were the analytical techniques used in this study, with the EViews 10 program being used for the fixed effect model.Research finding: The analysis results indicated that CSR had no significant effect on financial performance; earnings management could not moderate the influence of CSR on financial performance; leverage could moderate the effect of CSR on financial performanceTheoretical contribution/Originality: The study's findings offer insight and input for company management in terms of implementing CSR and its relation to company performance.Practitioner/Policy implication: The findings of this study should be helpful to stakeholders in selecting how to implement a CSR program in their company.Research limitation/Implication: This study only uses ROE as an indicator of financial performance, the research period is only 5 years, and CSR data is only based on what is stated in the company's financial statements.
Design Optimization and Characterization of Cold Neutron Imaging Detector Based on Novel Gadolinium Scintillation Glass Fiber Arrays and Infinity Corrected Optics

The use of scintillation glass fiber array in the reported cold neutron imaging detector can suppress lateral spreading of the scintillation light effectively and achieve a high spatial resolution while maintaining high detection efficiency. Theoretical analysis and experiments were combined to investigate influencing factors on the spatial resolution, the imaging contrast, the signal-to-noise ratio (SNR), and the detection efficiency with a cold neutron imaging detector made of new gadolinium scintillation glass fiber array and an infinity corrected optical readout system. The experiments were carried out on the Cold Neutron Radiography Facility at China Academy of Engineering Physics (CAEP). The cold neutron imaging detector made of 0.3-mm-thick Tb3+/Ce3+ co-doped Gd2O3 scintillation glass fiber array with a fiber diameter of 6 mm achieved a spatial resolution of 28.8 lp/mm (17.4 $\mu \text{m}$ ), an SNR of 28.6:1, and a cold neutron detection efficiency of 31.6%, i.e., a cold neutron absorption efficiency of 81.0%.
Difference between the optical flickering colours of cataclysmic variables and symbiotic recurrent novae

Institute of Astronomy and National Astronomical Observatory, Bulgarian Academy of Sciences, 72 Tsarigradsko shose,BG-1784, Soﬁa, BulgariaReceived 2 September 2014, accepted 2014 Dec 04Published online 2015 Mar 01Key words Stars: binaries – novae, cataclysmic variables – binaries: symbiotic – stars: individual: T CrB, RS OphWe performed simultaneous observations in 3 bands (UBV)of the ﬂickering variability of the recurrent novae RS Ophand T CrB at quiescence. Using new and published data, we compare the colours of the ﬂickering in cataclysmic variablesand symbiotic recurrent novae. We ﬁnd a difference between t he colours of the ﬂickering source in these two types ofaccreting white dwarfs. The detected difference is highly signiﬁcant with p−value≈2×10
Collagen characteristics affect the texture of pork Longissimus and Biceps femoris

Abstract Connective tissue is considered to influence the toughness of pork, but most studies on connective tissue focus on the loin muscle. Cooking loss, Warner–Bratzler shear force (WBSF), texture profile analysis (hardness, springiness, chewiness, resilience, and cohesiveness), total and insoluble collagen content, the percentage of type III collagen relative to the total of type I and III collagen, proteoglycan content and intramuscular fat (IMF) content were measured for pork Biceps femoris (BF) and Longissimus thoracis et lumborum (LTL) and Pearson’s correlation was performed. The results showed that BF had higher WBSF, resilience, total, and insoluble collagen content than LTL (P < 0.05). When considering both muscles, total and insoluble collagen content were positively correlated (P < 0.05) with WBSF (r = 0.47 and 0.49, respectively), hardness (r = 0.49 and 0.50, respectively), cohesiveness (r = 0.50 and 0.50, respectively), chewiness (r = 0.58 and 0.59, respectively) and resilience (r = 0.63 and 0.63, respectively). The percentage of type III collagen content was negatively correlated (P < 0.05) with WBSF (r = −0.68) and hardness (r = −0.58). Collagen content was correlated (P < 0.05) with WBSF (r = 0.75) and hardness (r = 0.61) in LTL and with cohesiveness (r = 0.74) and resilience (r = 0.63) in BF. Collagen characteristics differ between muscles and contribute to pork texture in both LTL and BF.
Self-Packaged Low-Loss Low-Pass Filter With Hexagonal Suspended Toroidal Inductors

This letter presents the design and analysis of the proposed hexagonal suspended toroidal inductors and the applications in a self-packaged low-loss low-pass filter (LPF). The characteristics of the proposed inductors are studied and analyzed with the developed <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-type equivalent circuit model. Compared to widely adopted spiral inductors, the proposed hexagonal suspended toroidal inductors feature improved quality factors (<inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>-factors) in experimental verifications. Following the developed theory and equivalent circuit model, several suspended toroidal inductors are designed and applied to a 5th-order lump self-packaged LPF. The filter achieves the passband insertion losses of < 0.49 dB and return losses of <inline-formula> <tex-math notation="LaTeX">$>14.7$ </tex-math></inline-formula> dB, which demonstrate the advantages of high <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>-factor of the proposed inductor topology.
Pricing postselection: the cost of indecision in decision theory

Postselection is the process of discarding outcomes from statistical trials that are not the event one desires. Postselection can be useful in many applications where the cost of getting the wrong event is implicitly high. However, unless this cost is specified exactly, one might conclude that discarding all data is optimal. Here we analyze the optimal decision rules and quantum measurements in a decision theoretic setting where a pre-specified cost is assigned to discarding data. We also relate our formulation to previous approaches which focus on minimizing the probability of indecision.
Comparative study of optimization algorithms on convolutional network for autonomous driving

he last 10 years have been the decade of autonomous vehicles. Advances in intelligent sensors and control schemes have shown the possibility of real applications. Deep learning, and in particular convolutional networks have become a fundamental tool in the solution of problems related to environment identification, path planning, vehicle behavior, and motion control. In this paper, we perform a comparative study of the most used optimization strategies on the convolutional architecture residual neural network (ResNet) for an autonomous driving problem as a previous step to the development of an intelligent sensor. This sensor, part of our research in reactive systems for autonomous vehicles, aims to become a system for direct mapping of sensory information to control actions from real-time images of the environment. The optimization techniques analyzed include stochastic gradient descent (SGD), adaptive gradient (Adagrad), adaptive learning rate (Adadelta), root mean square propagation (RMSProp), Adamax, adaptive moment estimation (Adam), nesterov-accelerated adaptive moment estimation (Nadam), and follow the regularized leader (Ftrl). The training of the deep model is evaluated in terms of convergence, accuracy, recall, and F1-score metrics. Preliminary results show a better performance of the deep network when using the SGD function as an optimizer, while the Ftrl function presents the poorest performances.
An Improved Theory for Microstrip Antennas and Applications. Part I.

Abstract : An improvement to a recently reported theory for the analysis of the pattern and impedance loci of microstrip antennas is developed. It yields a theory which is simple and inexpensive to apply. The fields in the interior of the antennnas are characterized in terms of a discrete set of modes. The poles corresponding to these modes are complex and depend on the losses in the antenna. The representation of the fields in terms of these modes in rigorous only for a bona fide cavity with no copper loss. The proper shift in the complex poles due to the addition of copper and radiative losses is approximated by lumping the latter two together with the dielectric loss to form an effective loss tangent. By so doing, it is found that the resulting expressions for impedance of the microstrip antenna is in good agreement with measured results for all modes and feed locations. The theory is applied to the evaluation of impedance variation with feed location, multiport analysis, and to design of circularly polarized microstrip antennas. (Author)
Symmetry breaking and the Scalar boson - evolving perspectives

The mechanism extending spontaneous symmetry breaking to gauge fields had a considerable impact on both theoretical and experimental elementary particle physics. It is corroborated by the discovery of the Z and the W, and by the precision electroweak tests. A detection of its Scalar boson(s) would not only constitute a direct verification of the mechanism, but knowledge of its couplings to known particles could pave the way to the world hitherto hidden beyond the Standard Model. These topics are discussed with emphasis on conceptual issues.
A Unified Approach to Geopotential Field Modeling

Abstract : It is shown that when both vector and gradient tensor components of a potential field are simultaneously available, inverse problems, such as determining the depth to the oceanic magnetic basement, can be split into a purely geometric problem, which seeks to determine the dimension and position parameters of one or more prisms and a purely geophysical problem, which seeks to determine the physical properties (i.e., the magnetization, polarization, density, etc.) of the prism. The geometrical problem is nonlinear and must be solved iteratively using standard stochastic or least-squares inversion techniques, while the geophysical problem is linear and may be solved by direct inversion once the geometric parameters have been established. Magnetic, Electric, Gravity, Inverse modeling, Poisson relations, Potential fields, Rectangular prisms.
Protein Supplementation Does Not Maximize Adaptations to Low-Volume High-Intensity Interval Training in Sedentary, Healthy Adults: A Placebo-Controlled Double-Blind Randomized Study

There is ample evidence that specific nutritional strategies can enhance adaptions to resistance and endurance training. However, it is still unclear whether post-session protein supplementation may increase the effects of low-volume high-intensity interval training (LOW-HIIT). We examined the impact of LOW-HIIT combined with protein vs. placebo supplementation on cardiometabolic health indices in sedentary healthy individuals. Forty-seven participants (31.1 ± 8.0 yrs) performed cycle ergometer LOW-HIIT (5–10x1 min at 80–95% maximum heart rate) for eight weeks and randomly received double-blinded 40 g of whey protein (PRO-HIIT, N = 24) or an isocaloric placebo (maltodextrin, PLA-HIIT, N = 23) after each session. The maximum oxygen uptake (VO2max, primary outcome) and several secondary cardiometabolic outcomes were determined pre-/post-intervention. VO2max increased in PRO-HIIT (+2.8 mL/kg/min, p = 0.003) and PLA-HIIT (+3.5 mL/kg/min, p < 0.001). Systolic and diastolic blood pressure decreased in PRO-HIIT (−7/3 mmHg, p < 0.05) and PLA-HIIT (−8/5 mmHg, p < 0.001). Gamma glutamyl transferase (−2 U/L, p = 0.003) decreased in PRO-HIIT and alanine aminotransferase (−3 U/L, p = 0.014) in PLA-HIIT. There were no significant between-group differences in any of the outcome changes. In conclusion, LOW-HIIT improved VO2max and other cardiometabolic markers irrespective of the supplementation condition. Post-session protein supplementation does not seem to provide any additional benefit to LOW-HIIT in improving cardiometabolic health in sedentary healthy individuals.
An attention-enhanced multi-modal deep learning algorithm for robotic compound fault diagnosis

Compound fault diagnosis plays a critical role in lowering the maintenance time and cost of industrial robots. With the advance of deep learning and industrial big data, a compound fault diagnosis model can be established through a data-driven approach. However, current methods mainly focus on the single fault diagnosis of assets, which cannot achieve satisfactory performance for compound fault diagnosis. This study proposes a compound fault diagnosis algorithm for an industrial robot based on multi-modal feature extraction and fusion. Firstly, the multi-head self-attention enhanced convolution neural network module and long short-term memory network module are adopted to learn the fault-related features from different perspectives simultaneously. The local and global features extracted by the aforementioned modules are then fused for subsequent compound fault classification. An experimental study was implemented based on real-world robotic sensor data. The experimental results indicated that the proposed multi-modal algorithm shows merits in compound fault diagnosis in comparison with other state-of-the-art methods.
Experimental evidence for large dynamic effects on the plasmon dispersion of subwavelength metal nanoparticle waveguides

We present angle- and frequency-resolved optical extinction measurements to determine the dispersion relation of plasmon modes on Ag and Au nanoparticle chains with pitches down to 75 nm. The large splitting between transverse and longitudinal modes and the band curvature are inconsistent with reported electrostatic near-field models and confirm that far-field retarded interactions are important, even for λ∕5-sized structures. The data imply that lower propagation losses, larger signal bandwidth, and larger maximum group velocity than expected can be achieved for wave vectors below the light line. We conclude that for the design of optical nanocircuits coherent far-field couplings across the entire circuit need to be considered, even at subwavelength feature sizes
Multi-Epitope-Based Vaccine Candidate for Monkeypox: An In Silico Approach

Currently, there are limited treatment options available for the monkeypox disease. We used a computational strategy to design a specific antigenic vaccine against pathogens. After using various immunoinformatic tools and filters, cytotoxic T-cell lymphocyte (CTL)-, helper T-cell lymphocyte (HTL)-, and interferon gamma (IFN-γ)-inducing epitopes, which comprised the vaccine, in addition to other parameters, such as antigenic and allergic profiles, were assessed to confirm the safety of the vaccine. However, vaccine interaction and stability with Toll-like receptors (TLRs) were assessed by dynamic simulation methods, and it was found that the constructed vaccine was stable. In addition, C-IMMSIM tools were used to determine the immune-response-triggering capabilities of the vaccine. These immunoinformatic findings reveal that constructed vaccine candidates may be capable of triggering an efficient immune response for monkeypox viral infections. However, experimental evaluation is required to verify the safety and immunogenic profile of constructed vaccines.
Idempotent Generation in the Endomorphism Monoid of a Uniform Partition

Denote by 𝒯n and 𝒮n the full transformation semigroup and the symmetric group on the set {1,…, n}, and ℰn = {1} ∪ (𝒯n∖𝒮n). Let 𝒯(X, 𝒫) denote the monoid of all transformations of the finite set X preserving a uniform partition 𝒫 of X into m subsets of size n, where m, n ≥ 2. We enumerate the idempotents of 𝒯(X, 𝒫), and describe the submonoid S = ⟨ E ⟩ generated by the idempotents E = E(𝒯(X, 𝒫)). We show that S = S1 ∪ S2, where S1 is a direct product of m copies of ℰn, and S2 is a wreath product of 𝒯n with 𝒯m∖𝒮m. We calculate the rank and idempotent rank of S, showing that these are equal, and we also classify and enumerate all the idempotent generating sets of minimal size. In doing so, we also obtain new results about arbitrary idempotent generating sets of ℰn.
Uniform distribution of sequences

( 1 ) {xn}z= Xn--Z_I Zin-Ztn-I is uniformly distributed mod 1, i.e., if ( 2 ) lim (1/N)A(x, N, {xn}z)-x (0x<_ 1), where A(x, N, {Xn)) denotes the number of indices n, l<=n<=N such that {x} is less than x. The ollowing distribution properties of the sequence (Xn)=(nO)(t an arbitrary positive real number) are well-known" (i) I Z--Zn_c and Z/Zn_xol as n-c, then (Xn) is uniformly distributed mod z (W. J. Le Veque [6]). (ii) If z-z_x is decreasing, then (Xn)is uniformly distributed modz for almost all t; this result also holds in the case (Xn)=(nr) for any fixed ’0 (H. Davenport and W. J. Le Veque [3]). (iii) If z/z_--. 1 as n--c and if the number of terms z with znN is less than c.N(c, a>0), then (x) is uniformly distributed modz for almost all t (H. Davenport and P. ErdSs [2]). In the following we prove a generalization of some of these results by an elementary method (cf. [7]). For this purpose we define a sequence (x) to be almost uniformly distributed mod z if there is an infinite sequence N<N<. of positive integers such that ( 3 ) lim (1/N)A(x, N, {x})= x (0x-<l)
Industry Differences in Productivity—In Agriculture and Tourism by Lake Balaton, Hungary

The paper compared the performance of firms in agriculture and in tourism in two countryside areas of Hungary, assessing 2613 firms for 16 years (2004–2019). The data are from tax reports of all firms of the analysed areas. Agriculture and countryside tourism depend on environmental factors, thus they are more seriously affected by adverse environmental events than other production or service industries. The research was aimed at identifying differences between the two industries, and reveal time patterns and size-related traits of performance. Labour force, sales revenues, total assets, labour productivity, and total factor productivity (TFP) were analysed with descriptive statistics and panel regression analysis. Results reveal that the performance of firms in these industries differ significantly regarding total assets, sales revenues, labour force, and labour productivity, but does not differ in TFP, and differences are associated either with average levels of indicator values or their temporal tendencies. Our results underline that firm performance considerably differs by firm size, smaller firms are generally more labour-efficient than larger ones, and labour efficiency is positively impacted by total asset level, but TFP is not. Agriculture was found to be not less efficient than tourism, contrary to general assumptions.