Miracle-dz/UniFAR-FTUs huggingface dataset:
Size Determination of Gold Clusters by Polyacrylamide Gel Electrophoresis in a Large Cluster Region

Polyacrylamide gel electrophoresis (PAGE) is used to separate the component of the glutathione protected gold clusters up to Au160 core size and compare the size with the mobility data from PAGE. Both electrospray mass spectrometry and transmission electron microscopy were systematically applied to analyze Au−glutathione clusters thus isolated. We have found a linear relationship between the mobility of the gold cluster compounds to the logarithm of the number of gold atoms of the core. Better fitting to the logarithm of the number of thiolate molecules adsorbed on the gold core was found and was expressed by a simple equation that bears conformation of ligand and charge density of clusters. Hence the mobility of the metallic clusters was correlated to the component of the ligand of the cluster.
A bis(2,2′-Bipyridine) (Dipyrido[3, 2-a:2′ 3′-c]Phenazine-N4N5) Ruthenium(II)-Based Electrochemiluminescence Biosensor for Evaluation of DNA Damage

The electrochemiluminescence of bis(2, 2′-bipyridine) (dipyrido[3, 2-a:2′ 3′-c]phenazine-N4N5) ruthenium(II) ([Ru(bpy)2(dppz)]2+) was used to monitor deoxyribonucleic acid (DNA) charge transfer with tri-n-propylamine as a coreactant. This system was used to measure damage to DNA induced by perfluorooctanoic acid. Fifteen-base pairs of double-stranded DNA with a thiol group at the 5′ end position were covalently bonded to a gold electrode. An electrochemiluminescence sensor was then constructed by incubating the modified gold electrode in [Ru(bpy)2(dppz)]2+ solution for 30 min. For comparison, single-stranded DNA, well-matched double-stranded DNA, and single base-mismatched double-stranded DNA were assembled on the gold surface. The results showed that the electrochemiluminescence behavior of the DNA sensors were unique. The electrochemiluminescence decreased when the [Ru(bpy)2(dppz)]2+-DNA ECL sensor was incubated in a perfluorooctanoic acid solution. The damage to DNA caused by perfluorooctanoic acid was monitored using a combination of DNA charge transfer theory and the interaction between DNA and [Ru(bpy)2(dppz)]2+. The detection limit for perfluorooctanoic acid was 1 × 10−12 mol/L. [Ru(bpy)2(dppz)]2+ was shown to be a sensitive electrochemiluminescence sensor for the determination of DNA damage.
Bulletin of the Geological Society of Greece

In the present study the relationship between Rn and hydrochemical parameters in groundwater samples with the intense tectonics that prevail in the broader region of Aigion were investigated. Radon concentrations were measured in water samples collected from the unconfined aquifer, hosted in Plio-Pleistocene deposits, along the major faults of the research area. The spatial distribution of radon concentrations revealed the existence of three distinct zones along Aigion, Pyrgaki and Helike faults, respectively. The first two zones are characterized by high radon concentrations, whereas the third by low radon concentrations. It is also shown that Rn and CO2 concentrations display similar spatial distribution suggesting a common origin for these two gases, with CO2 being the major carrier gas for radon in deep fluids. The deformation and fragmentation of rocks along the fault zones enables the circulation of those fluids resulting in elevated radon concentrations in groundwater. However, other factors, such as the mineralogical composition of the sediments along the fault planes may restrict this process. The distribution of radon along the fault zones suggests that radon measurements can be used as a tool for the detailed mapping of active faults and if combined with seismic data even as a tool for study earthquake prediction.
Phytochemical Analysis of Three Common Medicinal Plants (Gliricidia sepium, Melothria pendula, and Pithecellobium dulce) in the Philippines

Original Research Article Three common medicinal plants in the Philippines, Gliricidia sepium (madre de cacao), Melothria pendula (wild pipino), and Pithecellobium dulce (Camachile), were studied to determine their phytochemical components. Healthy, matured leaves of which were collected from Piat, Cagayan, thoroughly washed, air-dried, and then subjected for ethanolic extraction. Phytochemical analysis showed that G. sepium contains coumarins, saponins, steroids (cardiac glycosides), tannins, and terpenoids. M. pendula, on the other hand, possesses alkaloids, anthraquinones, quinones, saponins, steroids, tannins, terpenoids, and xanthoproteins. P. dulce, meanwhile, has alkaloids, anthraquinones, coumarins, quinones, saponins, steroids, tannins, terpenoids, and xanthoproteins. These secondary metabolites present on the leaf extract of the aforementioned plants have various pharmacological properties such as analgesic, anti-diarrheal, anti-inflammatory, and antimicrobial. This is the reason that these plants were widely used in the local community for the treatment and immediate remedy for common ailments such as fever, loose bowel, and simple wounds.
Employing Different Traps for Collection of Mosquitoes and Detection of Dengue, Chikungunya and Zika Vector, Aedes albopictus, in Borderline of Iran and Pakistan

Background: Southeastern Iran has been established as an area with the potential to harbor Asian tiger mosquito populations. In 2013, a few numbers of Aedes albopictus were detected in three sampling sites of this region. This field study was aimed to evaluate the efficacy of various traps on monitoring mosquitoes and status of this dengue vector, in five urban and 15 suburban/rural areas. Methods: For this purpose, four adult mosquito traps (BG-sentinel 2, bednet, Malaise, and resting box trap) were used and their efficacy compared. In addition, large numbers of CDC ovitraps were employed, within 12 months. Results: A total of 4878 adult samples including 22 species covering five genera were collected and identified from traps. It was not revealed any collection of Ae. albopictus. Statistical analysis showed no significant difference in meteorological variables between the two periods, the previous report and the current study. There were significant differences in the total number of mosquitoes collected by various traps in the region across different months. Conclusion: The resulting data collected here on the efficiency of the various trap types can be useful for monitoring the densities of mosquito populations, which is an important component of a vector surveillance system. While the presence of Ae. albopictus was determined in this potential risk area, there is no evidence for its establishment and further monitoring needs to be carried out.
Modeling the population and industry distribution impacts 1 of urban land use policies in Beijing 2

: Capable tools are desired for urban spatial policies planning in China to safeguard 3 its sustainable development strategy. This study develops an activity-based Land 4 Use/Transport Interaction (LUTI) model to forecast the urban activity impacts of the land-use 5 policies. Essentially, its endogenized and interactive features in residential and employment 6 distribution modeling mark it out from the traditional Lowry models. The LUTI model 7 proposed consists of four models, i.e., a transport sub-model, a residential location model, an 8 employment location model and a real estate rent model. It is then applied to the Beijing 9 metropolitan area to characterize the urban activity evolution trend under the land use policies 10 of recent years. The results show that with the increasing number of floorspace developed on 11 the outskirts, more residents and employers are relocating there and sub-centers are formed to 12 divide the service of central Beijing. This trend is consistent with the objective of government 13 planning to develop more sub-centers around central Beijing by decentralizing industries to 14 guide residential population growth patterns. The model provides a capable planning tool for 15 urban spatial policy makers and demonstrates its first success in Beijing scenario. 16
Fingerprint Detection on Counterfeit US$ Banknotes: The Importance of Preliminary Paper Examination

Two seizures of counterfeit 100 US$ bills related to the same indicative number were submitted for processing of latent fingerprints. On one group of notes, identifiable fingerprints could be detected by the routine application of amino acid reagents. In the second case, this technique gave no results, even on deliberately deposited prints. Fingerprints could be revealed, however, by cyanoacrylate fuming followed by magnetic powder. Comprehensive paper analysis showed that banknotes from both seizures differed remarkably by chemical composition as well as paper macroscopic properties. The difference in surface free energy (related to surface tension) of the banknotes in the two groups seemed to be the major factor responsible for the great variance in fingerprint detectability.
Engineering and impact of surface states on AlGaN/GaN-based hetero field effect transistors

This work investigates the impact and origin as well as the electrical behaviour of surface states of AlGaN/GaN-based heterostructure field effect transistors (HFETs). Different GaN-cap layers were grown on top of AlGaN-barrier layers, and the active transistor surface areas were treated chemically differently. The investigations show that one relevant surface state at the AlGaN/GaN surface is that of donor-like N-vacancies. Surface plasma treatments with O2- and N2-plasmas on structures with and without GaN-cap layers reveal very different electrical dc behaviour of AlGaN/GaN-based HFETs. Band structure simulations and considerations explain the different character of surface states and the impact on the dc channel current as well as the influence on threshold voltage and barrier height by Fermi-level pinning. N-vacancies on the surface of AlGaN/GaN HFETs are ionized and therefore very sensitive to N2-treatment, whereas on GaN/AlGaN/GaN surfaces they remain neutral and do not affect nS and ID significantly. Oxidation, however, also introduces acceptor-like surface states, which become ionized only in the case of GaN capping, leading to an additional positive charge at the upper heterojunction and increasing negative charge in the channel. It is further shown that 30 nm low-temperature grown GaN capping drastically reduces the gate leakage, leading to a transistor with insulated gate characteristics.
Nonlinear Estimation for Position-Aided Inertial Navigation Systems

In this work we solve the position-aided 3D navigation problem using a nonlinear estimation scheme. More precisely, we propose a nonlinear observer to estimate the full state of the vehicle (position, velocity, orientation and gyro bias) from IMU and position measurements. The proposed observer does not introduce additional auxiliary states and is shown to guarantee semi-global exponential stability. The performance of the observer is shown, through simulation, to overcome the state-of-the-art approach that assumes negligible accelerations.
STATISTICAL FITTING OF EVOLUTION MODELS TO ROTATION RATES OF SUN-LIKE STARS

We apply for the first time a two-dimensional fitting statistic, τ, to rotational evolution models (REMs) of stars (0.1 to 1.3 M ) on the period-mass plane. The τ 2 statistic simultaneously considers all cluster rotation data to return a goodness of fit, allowing for data-driven improvement of REMs. We construct data sets for Upper Sco, the Pleiades and Praesepe, to which we tune our REMs. We use consistently determined stellar masses (calculated by matching Ks magnitudes to isochrones) and literature rotation periods. As a first demonstration of the τ statistic, we find the best-fitting gyrochronology age for Praesepe, which is in good agreement with the literature. We then systematically vary three parameters which determine the dependence of our stellar wind torque law on Rossby number in the saturated and unsaturated regimes, and the location of the transition between the two. By minimising τ, we find best-fit values for each parameter. These values vary slightly between clusters, mass determinations and initial conditions, highlighting the precision of τ and its potential for constraining REMs, gyrochronology, and understanding of stellar physics. Our resulting REMs, which implement the best-possible fitting form of a broken power-law torque, are statistically improved on previous REMs using similar formulations, but still do not simultaneously describe the observed rotation distributions of the lowest masses, which have both slow and fast rotators by the Praesepe age, and the shape of the converged sequence for higher masses. Further complexity in the REMs is thus required to accurately describe the data.
Term-community-based topic detection with variable resolution

Network-based procedures for topic detection in huge text collections offer an intuitive alternative to probabilistic topic models. We present in detail a method that is especially designed with the requirements of domain experts in mind. Like similar methods, it employs community detection in term co-occurrence graphs, but it is enhanced by including a resolution parameter that can be used for changing the targeted topic granularity. We also establish a term ranking and use semantic word-embedding for presenting term communities in a way that facilitates their interpretation. We demonstrate the application of our method with a widely used corpus of general news articles and show the results of detailed social-sciences expert evaluations of detected topics at various resolutions. A comparison with topics detected by Latent Dirichlet Allocation is also included. Finally, we discuss factors that influence topic interpretation.
Efficient Multi-Objective Optimization for Deep Learning

Multi-objective optimization (MOO) is a prevalent challenge for Deep Learning, however, there exists no scalable MOO solution for truly deep neural networks. Prior work either demand optimizing a new network for every point on the Pareto front, or induce a large overhead to the number of trainable parameters by using hyper-networks conditioned on modiﬁable preferences. In this paper, we propose to condition the network directly on these preferences by augmenting them to the feature space. Furthermore, we ensure a well-spread Pareto front by penalizing the solutions to maintain a small angle to the preference vector. In a series of experiments, we demonstrate that our Pareto fronts achieve state-of-the-art quality despite being computed signiﬁcantly faster. Furthermore, we showcase the scalability as our method approximates the full Pareto front on the CelebA dataset with an EfﬁcientNet network at a tiny training time overhead of 7% compared to a simple single-objective optimization. We will make our code publicly available. 2
Recent bottomonium measurements in pp, p--Pb and Pb--Pb collisions at forward rapidity with ALICE at the LHC

In ultrarelativistic nucleus-nucleus collisions, a deconfined state of strongly interacting matter is thought to be produced, commonly known as the quark--gluon plasma (QGP). Quarkonia, bound states of a heavy quark and antiquark, are an important probe to study the properties of the QGP. At the LHC, bottomonium (b$\rm\overline{b}$) is of particular interest to study the QGP complementarily to the lighter charmonium (c$\rm\overline{c}$) system. In addition to the measurements in nucleus-nucleus collisions, reference measurements in proton-proton and proton-nucleus collisions have been also carried out in order to better understand the bottom quark production and cold nuclear matter effects. ALICE measures the bottomonium production in the dimuon decay channel at forward rapidity ($2.5<y_{\rm {lab}}<4.0$) with the muon spectrometer. In this contribution, the recent measurements of bottomonium nuclear modification factors and azimuthal anisotropies in Pb--Pb collisions are presented. The bottomonium production in p--Pb and pp collisions are also discussed.
Unveiling the broad-band spectral and temporal properties of PKS 0903-57 during its brightest flare

We carried a detailed spectral and temporal study of blazar, PKS 0903-57 using the Fermi -LAT and Swift-XRT/UVOT observations, during its brightest flaring period MJD 58931–58970. During this period, the maximum daily averaged γ-ray flux (F0.1−500GeV) of 9.42 × 10−6 ph cm−2 s−1 is observed on MJD 58951.5, the highest γ-ray flux detected from PKS 0903-57 till now. Several high-energy (HE) photons (> 10 GeV) consistent with the source location at high probability (> 99%) are detected, and the γ-ray lightcurve in the active state shows multiple substructures with asymmetric profile. In order to understand the possible physical scenario responsible for the flux enhancement, we carried a detailed broadband spectral study of PKS 0903-57 by choosing different flux states from its active period. Neglecting the multi-band variability in each of the selected time intervals, we could reproduce their averaged broadband SEDs with a one-zone leptonic model whose parameters were derived with a χ-fit. We found that the broadband SED during different flux states can be reproduced by the synchrotron, synchrotron-self-Compton (SSC) and ExternalCompton (EC) processes. The seed photons for EC process from BLR or IR torus provide acceptable fits to the GeV spectrum in all the flux states; however, the detection of HE photons together with the equipartition condition suggest that the EC/IR process is a more likely scenario. Further, a detailed comparison between the fit parameters shows that the flux enhancement from quiescent-state to the flaring-state is mostly related to increase in the bulk Lorentz factor of the emission region and change in the break energy of the source spectrum.
Exploiting Class Similarity for Machine Learning with Confidence Labels and Projective Loss Functions

Class labels used for machine learning are relatable to each other, with certain class labels being more similar to each other than others (e.g. images of cats and dogs are more similar to each other than those of cats and cars). Such similarity among classes is often the cause of poor model performance due to the models confusing between them. Current labeling techniques fail to explicitly capture such similarity information. In this paper, we instead exploit the similarity between classes by capturing the similarity information with our novel confidence labels. Confidence labels are probabilistic labels denoting the likelihood of similarity, or confusability, between the classes. Often even after models are trained to differentiate between classes in the feature space, the similar classes' latent space still remains clustered. We view this type of clustering as valuable information and exploit it with our novel projective loss functions. Our projective loss functions are designed to work with confidence labels with an ability to relax the loss penalty for errors that confuse similar classes. We use our approach to train neural networks with noisy labels, as we believe noisy labels are partly a result of confusability arising from class similarity. We show improved performance compared to the use of standard loss functions. We conduct a detailed analysis using the CIFAR-10 dataset and show our proposed methods' applicability to larger datasets, such as ImageNet and Food-101N.
Preparation of superfine down particles derived from down fiber wastes and their application as an efficient adsorbent toward acid brilliant scarlet 3R

Low-cost superfine down particles (SDP) were evaluated as an adsorbent for the removal of acid brilliant scarlet 3R (ABS-3R) dye from aqueous solutions. Scanning electron microscopy, particle size distribution, Brunauer–Emmett–Teller specific surface area, X-ray diffraction, Fourier transform infrared spectroscopy, and amino-acid analysis were used to characterize the structural characteristics of the adsorbent material. The effects of adsorption process parameters, including initial pH, adsorbent dose, initial dye concentration, adsorption time, and temperature, were systematically studied in batch adsorption experiments. Further, adsorption equilibrium data were modeled by Langmuir, Freundlich, and Dubinin–Radushkevich isotherms. The adsorption process followed the Langmuir isotherm model and the maximum adsorption capacity was 158.23 mg/g at 318 K. Kinetic studies at different temperatures showed that the pseudo-second-order kinetic model fitted well in correlation to the experimental results in comparison to the pseudo-first-order model. The activation energy of the adsorption process was 59.52 kJ/mol, using the Arrhenius equation, which indicated the chemisorption nature of ABS-3R adsorption onto SDP. Thermodynamic study showed that adsorption of ABS-3R was a spontaneous and endothermic process. In summary, SDP was found to be an efficient and eco-friendly adsorbent, which might be suitable for the removal of dyes from aqueous solutions.
ECG-TCN: Wearable Cardiac Arrhythmia Detection with a Temporal Convolutional Network

Personalized ubiquitous healthcare solutions require energy-efficient wearable platforms that provide an accurate classification of bio-signals while consuming low average power for long-term battery-operated use. Single lead electrocardiogram (ECG) signals provide the ability to detect, classify, and even predict cardiac arrhythmia. In this paper we propose a novel temporal convolutional network (TCN) that achieves high accuracy while still being feasible for wearable platform use. Experimental results on the ECG5000 dataset show that the TCN has a similar accuracy (94.2%) score as the state-of-the-art (SoA) network while achieving an improvement of 16.5% in the balanced accuracy score. This accurate classification is done with $27 \times$ fewer parameters and $37 \times$ less multiply-accumulate operations. We test our implementation on two publicly available platforms, the STM32L475, which is based on ARM Cortex M4F, and the GreenWaves Technologies GAP8 on the GAPuino board, based on $1 +8$ RISC-V CV32E40P cores. Measurements show that the GAP8 implementation respects the real-time constraints while consuming 0.10mJ per inference. With 9.91GMAC/s/W, it is $23.0 \times$ more energy-efficient and $46.85 \times$ faster than an implementation on the ARM Cortex M4F (0.43GMAC/s/W). Overall, we obtain 8.1% higher accuracy while consuming $19.6\times$ less energy and being $35.1 \times$ faster compared to a previous SoA embedded implementation.
3D gravity in a box

The quantization of pure 3D gravity with Dirichlet boundary conditions on a finite boundary is of interest both as a model of quantum gravity in which one can compute quantities which are ``more local" than S-matrices or asymptotic boundary correlators, and for its proposed holographic duality to T\overline{T}TT¯-deformed CFTs. In this work we apply covariant phase space methods to deduce the Poisson bracket algebra of boundary observables. The result is a one-parameter nonlinear deformation of the usual Virasoro algebra of asymptotically AdS_33 gravity. This algebra should be obeyed by the stress tensor in any T\overline{T}TT¯-deformed holographic CFT. We next initiate quantization of this system within the general framework of coadjoint orbits, obtaining — in perturbation theory — a deformed version of the Alekseev-Shatashvili symplectic form and its associated geometric action. The resulting energy spectrum is consistent with the expected spectrum of T\overline{T}TT¯-deformed theories, although we only carry out the explicit comparison to \mathcal{O}(1/\sqrt{c})𝒪(1/c) in the 1/c1/c expansion.