Miracle-dz/UniFAR-FTUs huggingface dataset:
Extreme non-Arens regularity of the group algebra

The Banach algebras of Harmonic Analysis are usually far from being Arens regular and often turn out to be as irregular as possible. This utmost irregularity has been studied by means of two notions: strong Arens irregularity, in the sense of Dales and Lau, and extreme non-Arens regularity, in the sense of Granirer. Lau and Losert proved in 1988 that the convolution algebra {L^{1}(G)} is strongly Arens irregular for any infinite locally compact group. In the present paper, we prove that {L^{1}(G)} is extremely non-Arens regular for any infinite locally compact group. We actually prove the stronger result that for any non-discrete locally compact group G, there is a linear isometry from {L^{\infty}(G)} into the quotient space {L^{\infty}(G)/\mathcal{F}(G)}, with {\mathcal{F}(G)} being any closed subspace of {L^{\infty}(G)} made of continuous bounded functions. This, together with the known fact that {\ell^{\infty}(G)/\mathscr{W\! A\! P}(G)} always contains a linearly isometric copy of {\ell^{\infty}(G)}, proves that {L^{1}(G)} is extremely non-Arens regular for every infinite locally compact group.
The challenges of modelling microphysics: ambipolar diffusion, chemistry, and cosmic rays in MHD shocks

From molecular clouds to protoplanetary disks, non-ideal magnetic effects are important in many astrophysical environments. Indeed, in star and disk formation processes, it has become clear that these effects are critical to the evolution of the system. The efficacy of non-ideal effects are, however, determined by the complex interplay between magnetic fields, ionising radiation, cosmic rays, microphysics, and chemistry. In order to understand these key microphysical parameters, we present a one-dimensional non-ideal magnetohydrodynamics code and apply it to a model of a time-dependent, oblique, magnetic shock wave. By varying the microphysical ingredients of the model, we find that cosmic rays and dust play a major role, and that, despite the uncertainties, the inclusion of microphysics is essential to obtain a realistic outcome in magnetic astrophysical simulations.
A γ-ray Quasi-periodic Modulation in the Blazar PKS 0301–243?

We report a nominally high-confidence γ-ray quasi-periodic modulation in the blazar PKS 0301–243. For this target, we analyze its Fermi-LAT Pass 8 data from 2008 August to 2017 May. Two techniques, i.e., maximum likelihood optimization and exposure-weighted aperture photometry, are used to build the γ-ray light curves. Then, both the Lomb–Scargle periodogram and the weighted wavelet Z-transform are applied to the light curves to search for period signals. A quasi-periodicity with a period of 2.1 ± 0.3 yr appears at the significance level of , although it should be noted that this putative quasi-period variability is seen in a data set that is barely four times longer. We speculate that this γ-ray quasi-periodic modulation may be evidence of a binary supermassive black hole.
Development of Shrimp Freshness Indicating Films by Embedding Anthocyanins-Rich Rhododendron simsii Flower Extract in Locust Bean Gum/Polyvinyl Alcohol Matrix

Freshness indicating films containing anthocyanins are one type of smart packaging technology. Anthocyanins in the films can show visual color changes when food spoilage occurs, thereby indicating the freshness degree of food in real-time. Rhododendron simsii is a landscape plant with attractive flowers that are abundant in anthocyanins. In this study, smart packaging films were prepared by embedding 2% and 4% R. simsii flower anthocyanins (RA) in locust bean gum- (LBG) and polyvinyl alcohol- (PVA) based matrices. The micro-structure, barrier, mechanical, thermal, antioxidant, and color-changeable properties of the films were determined. The potential application of the films in indicating the freshness of shrimp at 4 °C was also investigated. Results showed that the RA interacted with the LBG/PVA matrices through hydrogen bonds, which significantly improved the barrier, mechanical, thermal, antioxidant, pH-sensitive, and ammonia-sensitive properties of the films. Meanwhile, the performance of the films was remarkably influenced by the content of the RA. The film containing 4% RA had the highest light blocking ability, tensile strength (38.32 MPa), elongation at break (58.18%), and antioxidant activity, and also showed the lowest water vapor permeability (22.10 × 10−11 g m−1 s−1 Pa−1) and oxygen permeability (0.36 cm3 mm m−2 day−1 atm−1). The films containing 2% and 4% RA could effectively change their colors when the level of total volatile basic nitrogen in the shrimp exceeded the safe value, which demonstrated the suitability of the films for indicating the freshness degree of shrimp.
Extract of Mallotus oppositifolius (Geiseler) Müll. Arg. increased prefrontal cortex dendritic spine density and serotonin and attenuated para-chlorophenylalanine-aggravated aggressive and depressive behaviors in mice

Background/Aim: Depression-related aggression is linked to serotonin (5-HT) and dendritic spine alterations. Although Mallotus oppositifolius extract (MOE) has potential for reducing this effect, its specific role remains uncertain. Herein, we evaluated this potential and associated alterations in the brain. Methods: A standard resident-intruder model of para-chlorophenylalanine (pCPA)-induced depression-associated aggression in male ICR mice was used. The resident mice received pCPA (300 mg/kg, i. p.) for 3 consecutive days while saline-treated mice served as negative control. The pCPA aggressive mice were subsequently treated orally with either MOE (30, 100, 300 mg/kg), fluoxetine (20 mg/kg), tryptophan (20 mg/kg) or saline (untreated pCPA group) for 28 days. Locomotor activity was assessed using open field test. Serotonin (5-HT) levels in mice brain and phytochemical fingerprint of MOE were determined by high performance liquid chromatography (HPLC) while gas chromatography-mass spectrometry (GC-MS) was used to identify constituents of MOE. Dendritic spine density and morphology were evaluated using Golgi-Cox staining technique and analyzed with ImageJ and Reconstruct software. Results: Administration of pCPA induced aggressive behavior in mice, evidenced by increased attack behaviors (increased number and duration of attacks), which positively correlated with squeaking and tail rattling. MOE treatment significantly reduced these characteristics of aggression in comparison with vehicle (non-aggressive) and untreated pCPA groups (p < 0.001), and also reduced social exploration behavior. Although the behavioral effects of MOE were comparable to those of fluoxetine and tryptophan, these effects were quicker compared to fluoxetine and tryptophan. Additionally, MOE also markedly increased 5-HT concentration and dendritic spine density in the prefrontal cortex relative to vehicle and untreated pCPA groups (p < 0.05). Interestingly, these behavioral effects were produced without compromising locomotor activity. GC-MS analysis of the MOE identified 17 known compounds from different chemical classes with anti-inflammatory, antioxidant, neuroprotective and antidepressant activities, which may have contributed to its anti-aggressive effect. Conclusion: MOE decreased depression-associated aggressive behavior in mice via increased 5-HT concentration and dendritic spine density in the prefrontal cortex. The MOE-mediated effects were faster than those of fluoxetine and tryptophan. Our finding suggests that MOE may have clinical promise in decreasing aggressive and depressive behaviors. Graphical Abstract
CLEASE: a versatile and user-friendly implementation of cluster expansion method

Materials exhibiting a substitutional disorder such as multicomponent alloys and mixed metal oxides/oxyfluorides are of great importance in many scientific and technological sectors. Disordered materials constitute an overwhelmingly large configurational space, which makes it practically impossible to be explored manually using first-principles calculations such as density functional theory due to the high computational costs. Consequently, the use of methods such as cluster expansion (CE) is vital in enhancing our understanding of the disordered materials. CE dramatically reduces the computational cost by mapping the first-principles calculation results on to a Hamiltonian which is much faster to evaluate. In this work, we present our implementation of the CE method, which is integrated as a part of the atomic simulation environment (ASE) open-source package. The versatile and user-friendly code automates the complex set up and construction procedure of CE while giving the users the flexibility to tweak the settings and to import their own structures and previous calculation results. Recent advancements such as regularization techniques from machine learning are implemented in the developed code. The code allows the users to construct CE on any bulk lattice structure, which makes it useful for a wide range of applications involving complex materials. We demonstrate the capabilities of our implementation by analyzing the two example materials with varying complexities: a binary metal alloy and a disordered lithium chromium oxyfluoride.
CP violation in the hadronic Ks meson decays

Discrete symmetries as parity P, charge conjugation C and time reversal T, as well as their combinations such as CP and CPT play a fundamental role in particle physics. The CP symmetry violation was discovered unexpectedly in 1964 during the regeneration studies of the neutral K mesons, and result in a far–reaching consequences. In the framework of the Standard Model it implies the existence of the third generation of quarks. Moreover, it is a very important mechanism which could have an essential contribution to the asymmetry between matter and antimatter in the Universe. Parameters describing CP violation in neutral kaon decays were measured with a good precision and at present the main experimental effort is focused on studies of the neutral B and D meson systems. However, there are still several interesting open issues in the kaon physics, like rare Ks meson decays. This work is focused on the measurement of the rare CP violating Ks→3π0 decay branching ratio based on the data sample gathered with the KLOE detector operating at the φ–factory DAΦNE in the Italian National Center for Nuclear Physics in Frascati.
Using the power of machine learning in sales research: process and potential

Abstract This study addresses the potential for improving the accuracy, scope, and value of sales research through the application of data mining and machine learning algorithms. By examining prior research, identifying opportunities for improvement, and assessing gaps that can benefit from machine learning, research and application are made more accessible for sales researchers and managers. Machine learning can address important sales research questions that cannot be answered with the same accuracy or efficiency as traditional research methods. This study demonstrates the benefits of the methods through an example of application to the prediction of salesforce performance based on behavioral, attitudinal, and demographic data. This includes future research ideas, usage cases, and applications where machine learning could advance sales research and management. Machine learning and predictive analytics methods have multiple applications, including in B2C and B2B market contexts and for companies and independent sales teams.
Algorithms and Dynamic Data Structures for Basic Graph Optimization Problems

Graph optimization plays an important role in a wide range of areas such as computer graphics, computational biology, networking applications and machine learning. Among numerous graph optimization problems, some basic problems, such as shortest paths, minimum spanning tree, and maximum matching, are the most fundamental ones. They have practical applications in various fields, and are also building blocks of many other algorithms. Improvements in algorithms for these problems can thus have a great impact both in practice and in theory. In this thesis, we study a number of graph optimization problems. The results are mostly about approximation algorithms solving graph problems, or efficient dynamic data structures which can answer graph queries when a number of changes occur. Much of my work focuses on the dynamic subgraph model in which there is a fixed underlying graph and every vertex can be flipped "on" or "off". The queries are based on the subgraph induced by the "on" vertices. Our results make significant improvements to the previous algorithms of these problems. The major results are listed below. • Approximate Matching. We give the first linear time algorithm for computing approximate maximum weighted matching for arbitrarily small approximation ratio. • d-failure Connectivity Oracle. For an undirected graph, we give the first space-efficient data structure that can answer connectivity queries between any pair of vertices avoiding d other failed vertices in time polynomial in d log n. • (Max, Min)-Matrix Multiplication. We give a faster algorithm for the (max, min)-matrix multiplication problem, which has a direct application to the all-pairs bottleneck paths (APBP) problem. • Dual-failure Distance Oracle. For a given directed graph, we construct a data structure of size O(n²) which can efficiently answer distance and shortest path queries in the presence of two node or link failures. • Dynamic Subgraph Connectivity. We give the first subgraph connectivity structure with worst-case sublinear time bounds for both updates and queries. • Bounded-leg Shortest Path. We give an algorithm for preprocessing a directed graph in O(n³) time in order to answer approximate bounded leg distance and bounded leg shortest path queries in merely sub-logarithmic time.
An Analysis of Transcriptomic Burden Identifies Biological Progression Roadmaps for Hematological Malignancies and Solid Tumors

Biological paths of tumor progression are difficult to predict without time-series data. Using median shift and abacus transformation in the analysis of RNA sequencing data sets, natural patient stratifications were found based on their transcriptomic burden (TcB). Using gene-behavior analysis, TcB groups were evaluated further to discover biological courses of tumor progression. We found that solid tumors and hematological malignancies (n = 4179) share conserved biological patterns, and biological network complexity decreases at increasing TcB levels. An analysis of gene expression datasets including pediatric leukemia patients revealed TcB patterns with biological directionality and survival implications. A prospective interventional study with PI3K targeted therapy in canine lymphomas proved that directional biological responses are dynamic. To conclude, TcB-enriched biological mechanisms detected the existence of biological trajectories within tumors. Using this prognostic informative novel informatics method, which can be applied to tumor transcriptomes and progressive diseases inspires the design of progression-specific therapeutic approaches.
Analisis perbandingan tipe belitan terhadap nilai parameter motor induksi satu fasa

ABSTRAK Motor induksi merupakan salah satu motor listrik yang luas penggunaannya. Salah satu jenis motor induksi adalah motor induksi satu fasa. Pada kondisi tertentu motor induksi perlu dilakukan rewinding pada kumparannya. Proses rewinding sebelumnya harus ditentukan jumlah kutub, tipe belitan, dimensi konduktor, serta jumlah lilitnya. Praktik di lapangan ketika melakukan proses rewinding umummya hanya memperhatikan jumlah kutub, akan tetapi tipe belitan tidak begitu diperhatikan secara khusus. Pada dasaranya setiap tipe belitan menghasilkan gaya gerak magnit (mmf) yang berbeda-beda, yang mana mmf tersebut mengandung komponen fundamental dan komponen harmonisanya. Hal ini akan berakibat fluksi yang dihasilkan juga berbeda. Dimana fluksi juga mempunyai peran pada nilai parameter motor induksi satu fasa. Pada penelitian ini dilakukan proses rewinding pada dua motor induksi dengan konstruksi yang sama, motor induksi pertama (M1) dengan tipe belitan terbagi-skrew dan motor induksi kedua (M2) dengan tipe belitan terpusat terdistribusi, kemudian dilakukan pengujian untuk mengetahui paramater motor induksi hasil rewinding. Hasil pengujian didapatkan perbedaan nilai reaktansi dimana M1 nilai reaktansi kumparan stator dan rotornya berturut-turut 5,71 Ω dan 5,71 Ω, pada M2 nilai reaktansi stator dan rotornya berturut-turut 5,98 Ω dan 5,98 Ω. Analisis perbedaan nilai reaktansi motor induksi tersebut dilakukan analisis finite element menggunakan perangkat lunak FEMM 4.2. ABSTRACT The single-phase induction motor is one of the most widely used electric motors. Under certain conditions, the induction motor needs to be rewinded on the coil. The rewinding process must determine the number of poles, the type of winding, the dimensions of the conductor, and the number of turns. Generally, when carrying out the rewinding process, the winding type is not given much special attention. Where each type of winding produces a different magnetomotive force (mmf). This will result in different fluxes resulting in different parameter values for single-phase induction motors. In this study, a comparison of the parameters of an induction motor with the same construction and with different winding types will be carried out. The first motor (M1) is of the screw-shared winding type and the second motor (M2) is of the distributed concentrated winding type. The test results show a difference in the reactance value where M1 the reactance values of the stator and rotor coils are 5.71 Ω and 5.71 Ω, respectively, while in M2 the stator and rotor reactance values are 5.98 Ω and 5.98 Ω, respectively. The difference in reactance values was carried out by finite element analysis using FEMM 4.2.
Freeform Wide Field-of-View Spaceborne Imaging Telescope: From Design to Demonstrator

Wide field-of-view imaging optics offer a huge potential for space-based Earth observation enabling the capture of global data. Reflective imaging telescopes are often favored, as they do not show chromatic aberrations and are less susceptible to radiation darkening than their refractive counterparts. However, the main drawback of reflective telescopes is that they are limited with respect to field-of-view while featuring large dimensions. We propose the use of freeform optics to maximize the field of view while maintaining diffraction-limited image quality and minimizing system dimensions. In this paper, we present a novel freeform wide field-of-view reflective telescope, starting from the optical design, and continuing to tolerancing analysis and manufacture, towards a proof-of-concept demonstrator. The novel telescope features a full field-of-view of 120° while showing an exceptional spatial resolution of 2.6 km and fitting within 1 CubeSat unit. To the best of our knowledge, this is the widest field-of-view that has ever been realized for a space-based telescope, nearly reaching Earth observation from limb to limb from an altitude of about 700 km. We hope this design paves the way for future space missions enabling improved Earth observation and leading to enhanced monitoring of climate and climate change.
High accuracy calculation and data quality evaluation of 1 ship emissions based on the sniffer method

More attention has been paid to the air pollution caused by ship emissions; hence the 7 establishment of accurate emission inventories is an important means to assess the impact on the 8 environment and human beings. The emission factor is an important parameter in the process of 9 compiling the ship emission inventory, yet there is some uncertainty in its estimation based on the sniffer 10 method. In this study, taking the calculation of SO 2 emission factors as an example and aiming at the 11 selection of gas measurement values using the sniffer method, the concept of standard deviation of peak 12 density was proposed to determine the optimal integral interval length of the measured values of SO 2 and 13 CO 2 . Then, the improved Manhattan distance was used to characterize the position of the peak points in 14 the SO 2 and CO 2 average series. Using the dynamic time warping algorithm , the corresponding 15 relationship of the peak points in the average series of the measured gases was determined, and the global 16 optimal peak points were selected from it. To evaluate the credibility of calculated emission factors, 16 17 evaluation indexes that reflect the characteristics of the measured data were selected. The confidence 18 interval of 95% of each evaluation index was calculated using self-development sampling of the 19 measured data, and the evaluation result of the evaluation index for the quality of the measured data was 20 obtained. Combined with the data quality label, the indexes with high correct rate were screened. Finally, 21 the evaluation scores were determined according to these selected indexes. We collected a total of 148 22 sets of "SO 2 +CO 2 " measurement data between 2019 and 2021 using the unmanned aerial vehicle sniffing 23 monitoring system in the Waigaoqiao Port area of Shanghai, China for verification using the method 24 proposed in this study. The results show that for this data set, 12 s is the most suitable integral length, 25 with which the algorithm can automatically calculate the emission factor. The screening results of the 26 global optimal peak points of 129 factor of ships mainly focused on different conditions such as time, region, fuel, engine, ship type, and 30 navigation status. Our in-depth study proposes a high accuracy ship emission factors calculation method 31 and an evaluation of the quality of the measurement data that reduces uncertainty in the current sniffer 32 technique monitoring ship emission research. measurement data show a trend of almost synchronous change with 492 a peak, hence both the Euclidean distance and the improved Manhattan distance give the appropriate 493 different conditions. However, there is little attention and research 604 on improving the accuracy, confidence, and automation of the calculation methods. In this study, we propose a high accuracy calculation of ship emission factors and an evaluation of the
Resonant two-site tunneling dynamics of bosons in a tilted optical superlattice

We study the nonequilibrium dynamics of a one-dimensional Bose-Hubbard model in a gradient potential and a superlattice, beginning from a deep Mott insulator regime with an average filling of one particle per site. Studying a quench that is near resonance to tunneling of the particles over two lattice sites, we show how a spin model emerges consisting of two coupled Ising chains that are coupled by interaction terms in a staggered geometry. We compare and contrast the behavior in this case with that in a previously studied case where the resonant tunneling was over a single site. Using optimized tensor network techniques to calculate finite-temperature behavior of the model, as well as finite-size scaling for the ground state, we conclude that the universality class of the phase transition for the coupled chains is that of a tricritical Ising point. We also investigate the out-of-equilibrium dynamics after the quench in the vicinity of the resonance and compare dynamics with recent experiments realized without the superlattice geometry. This model is directly realizable in current experiments and reflects a general way to realize spin models with ultracold atoms in optical lattices.