Miracle-dz/UniFAR-FTUs huggingface dataset:
Quarter-BPS black holes in AdS 4 -NUT from N = 2 gauged supergravity

: We study N = 2 gauged supergravity with U(1) gauge group coupled to n v vector multiplets and ﬁnd quite general analytic solutions for quarter-BPS black holes with mass, NUT and dyonic Maxwell charges. The solutions we ﬁnd have running scalar ﬁelds and ﬂow in the IR region to a horizon geometry of the form AdS 2 × Σ g .
Heavy quark density in N = 4 SYM: from hedgehog to Lifshitz spacetimes

: We study the eﬀect of an O ( N 2 ) density of heavy quarks in strongly coupled N = 4 SUSY Yang-Mills theory in the large N limit. This is achieved in the type IIB supergravity dual by introducing a uniformly smeared density of macroscopic string sources stretching to the boundary of AdS 5 × S 5 . The backreacted system exhibits a ﬂow from an AdS 5 “hedgehog” geometry to a scaling Lifshitz-like solution Lif 5 × S 5 with dynamical critical exponent z = 7, wherein the scaling symmetry is broken by a logarithmic running dilaton. We ﬁnd an exact black brane solution within the scaling regime which describes the low temperature thermodynamics of the system.
Localization of the four-dimensional N = 4 SYM to a two-sphere and 1/8 BPS Wilson loops

: We localize the four-dimensional N = 4 super Yang-Mills theory on S 4 to the two-dimensional constrained Hitchin/Higgs-Yang-Mills (cHYM) theory on S 2 . We show that expectation values of certain 1/8 BPS supersymmetric Wilson loops on S 2 in the 4d N = 4 SYM is captured by the 2d cHYM theory. We further argue that expectation values of Wilson loops in the cHYM theory agree with the prescription “two-dimensional bosonic Yang-Mills excluding instanton contributions”. Hence, we support the recent conjecture by Drukker, Giombi, Ricci and Trancanelli on the 1/8 BPS Wilson loops on S 2 in the 4d N = 4 SYM.
The generalized correlation method for estimation of time delay

A maximum likelihood (ML) estimator is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise. This ML estimator can be realized as a pair of receiver prefilters followed by a cross correlator. The time argument at which the correlator achieves a maximum is the delay estimate. The ML estimator is compared with several other proposed processors of similar form. Under certain conditions the ML estimator is shown to be identical to one proposed by Hannan and Thomson [10] and MacDonald and Schultheiss [21]. Qualitatively, the role of the prefilters is to accentuate the signal passed to the correlator at frequencies for which the signal-to-noise (S/N) ratio is highest and, simultaneously, to suppress the noise power. The same type of prefiltering is provided by the generalized Eckart filter, which maximizes the S/N ratio of the correlator output. For low S/N ratio, the ML estimator is shown to be equivalent to Eckart prefiltering.
‘More tangible and less theoretical’: Understandings and experiences of neighbourhood-led Mutual Aid groups during the COVID-19 pandemic

ABSTRACT This exploratory study sought to understand the role of Mutual Aid groups during the Covid-19 crisis. Group members were approached through convenience sampling across London and Leicester. Fifteen interviews took place from June to August 2020. Data were analysed using Thematic Analysis. Groups were based on solidarity not charity. Most were delimited by geographic ward and provided rapid support to support neighbours with urgent material and health needs, primarily food support, collecting medical prescriptions and providing telephone companionship. While many groups successfully collaborated with community projects, relationships with local authorities were often difficult, though not always. Local leaders and policymakers should seek to establish effective collaborations between Covid-19 Mutual Aid groups and local authorities to ensure essential material and health needs at a neighbourhood level are identified and met.
Preparation and Cellular Absorption of Zinc-chelating Peptides Derived from Sika Deer Blood

In order to prepare a zinc nutritional fortifier which was easily absorbed by human body and improved the utilization rate of sika deer blood. In this research, response surface methodology (RSM) was used to optimize the preparation conditions of zinc chelate sika deer blood polypeptide (SDBP). The peak chelated rate was 82.1% and zinc content was 21.3mg/mL. Used deer blood and zinc sulfate as raw materials and zinc chelated rate as an indicator, the effect of pH, reaction time, peptide zinc mass ratio and reaction temperature on zinc chelating rate were investigated by single factor text. The optimal condition for the chelation reaction was that mass ratio of peptide: zinc 2:1, pH 6 and 60°C for 60 min. The structure of zinc chelated by SDBP was characterized by UV, FTIR, SEM, molecular weight and particle size analysis elt. FTIR proved that SDBPCZ had sufficient metal binding sites. The bioavailability of zinc ion in sika deer blood peptide chelated zinc(SDBPCZ) was determined by simulating gastrointestinal digestion and absorption in vitro. Experimental synthesis showed that SDBPCZ exhibited better zinc solubility and had higher dialyzable than ZnSO 4. These results might provide insights into the methods for developing functional foods such as zinc-fortified.
Irradiation of hydrophobic coating materials by gamma rays and protons: space applications

The responses of hydrophobic silicone-based coatings following irradiation by Co-60-gamma-rays are reported. The dimethylsilicone (DMS) resin coatings consisted of neat samples and samples incorporating semiconductor metal oxide (SMO) irradiated at photon energies of 1.17 and 1.33 MeV. Pre-and post-irradiation measurements indicated that at a total dose of ~ 185 krad(Si) there was no significant change to the coating static hydrophobic contact angles, surface molecular structure and biocide neutralization efficiency. The data was compared with previously irradiated and reported DMS/SMO coatings at a proton fluence of ~1.5 x 1012 p/cm2. Potential space applications for the radiation resistant coating self- cleaning properties are presented as well as a discussion of other environmental testing required to qualify the technology for transition to photonic space applications.
Effective One-Class Classifier Model for Memory Dump Malware Detection

Malware complexity is rapidly increasing, causing catastrophic impacts on computer systems. Memory dump malware is gaining increased attention due to its ability to expose plaintext passwords or key encryption files. This paper presents an enhanced classification model based on One class SVM (OCSVM) classifier that can identify any deviation from the normal memory dump file patterns and detect it as malware. The proposed model integrates OCSVM and Principal Component Analysis (PCA) for increased model sensitivity and efficiency. An up-to-date dataset known as “MALMEMANALYSIS-2022” was utilized during the evaluation phase of this study. The accuracy achieved by the traditional one-class classification (TOCC) model was 55%, compared to 99.4% in the one-class classification with the PCA (OCC-PCA) model. Such results have confirmed the improved performance achieved by the proposed model.
DYNAMIC PERFORMANCE OF THE LEBLANC BALANCER FOR AUTOMATIC WASHING MACHINES

The paper describes a high-speed camera and a Particle Image Velocimetry (PIV) technique used on a transparent liquid balancing device for washing machines. Experimental results indicate that the baffle-liquid interaction renders fluid modes of vibration of circumferential and axial type. This complex swirl flow is comprised of two inertial waves; one of such waves is synchronous with the rigid body motion, while the other is a fluid backward traveling wave, thus enhancing the system damping capability. This damping phenomenon was revealed by the fluid flow visualization and Particle Image Velocimetry (PIV) technique employed. NOMENCLATURE
Assimilation of GNSS Zenith Total Delay in NAVGEM

A new data source from ground‐based stations that track global navigation satellite system (GNSS) transmitters has been implemented in the Navy Global Environmental Model (NAVGEM) with the NRL Atmospheric Variational Data Assimilation System‐Accelerated Representer. The observable is the ground‐based zenith total delay (ZTD) at each ground station. This ground‐based GNSS ZTD represents the tropospheric delay of the propagation of GNSS radio L‐band signal between the transmitters and the ground stations after correcting for ionospheric effects. Here, we present the implementation procedure, quality control, single observation test, bias correction scheme, and data impact assessment. One of the critical elements in the quality control scheme is to correct for the difference between the observing ground station elevation and the numerical model terrain. A single observation test shows comparable impact from this new data source to a single radiosonde observation at a single level. The ZTD biases estimated from a 6‐month experiment run are generally small, but have a dependency on the processing center and are computed separately for each station. The forecast sensitivity to observation impact diagnosis from a 3‐month experiment demonstrates that a single ZTD observation shows similar impact as the average impact from a single tangent point of a GNSS Radio Occultation profile. The assimilation of ZTD observations also significantly improves the forecast skill by 0.25%–0.75% for wind, temperature, and precipitable water and by 1%–2% for geopotential height in the Southern Hemisphere beyond 3 days.
Grant-Free Random Access in Cell-Free Massive MIMO Systems With UE Detection Thresholds: A Stochastic Geometry Approach

In this paper, we analyze the grant-free random access (GFRA) in cell-free massive multiple-input multiple-output (CF-mMIMO) systems. Unlike previous works on GFRA that regard all user equipments (UEs) selecting the same pilot as undetectable, we give a more accurate model that the access point (AP) can detect the strongest UE when its signal-to-interference-plus-noise ratio (SINR) exceeds a threshold. On top of this, we also define the concept of effective access that a UE is successfully detected by APs around it within a limited area. With tools from stochastic geometry, the probability of UE effective access and the minimum required AP spatial density that satisfies UEs' access delay constraints are derived. It is found that increasing the AP antenna number from 1 to 2 can significantly improve the UE access probability and reduce the required AP number, while this improvement decays quickly as the antenna number keeps growing, which works more obviously when the access delay constraint is strict or the pilot length is short.
Self-consistent treatment of gas heating in modeling of a coaxial DBD in atmospheric pressure CO2

This work is devoted to the numerical study of characteristics of dielectric barrier discharge maintained in a coaxial reactor in atmospheric pressure CO2 . The numerical model is based on the drift-diffusion theory of gas discharges, and takes into account the gas heating in a self-consistent manner. The effect of incorporating gas heating into the discharge properties, specifically, on CO2 decomposition, is investigated for wide range of amplitude and frequency of the applied voltage. Calculations revealed a significant effect of gas heating on CO2 conversion. Calculations with a constant (room) gas temperature led to a strong overestimation of CO2 conversion level.
Inertial-confinement fusion with fast ignition

The fast ignitor scheme consists of three stages and relies on ignition of a part of the compressed fusion fuel of an inertial–confinement fusion capsule by an external trigger. A conventional fusion target is imploded uniformly either by a soft X–ray or laser pulse. A hole is bored through the corona plasma resulting in a channel that leads to the edge of the compressed core. This channel is produced by the ponderomotive force and relativistic effects of a high intensity laser pulse with a duration of tens of picoseconds. Finally, an ultraintense picosecond laser pulse is guided through the channel to the critical density and converted to an MeV electron beam. The electron beam then propagates from the critical density to the high–density core igniting the compressed fusion fuel. As a lower compression ratio is required with this scheme the uniformity of driver and the symmetry requirements of the implosion are less stringent. There are, however, several critical plasma and laser physics issues involved in this scheme, including hole boring, electron–beam generation and propagation and the production of a laser pulse with a duration of 1 to 10 ps and an energy between 10 and 100 kJ.
Item Selection for a New Health-Related Quality of Life Measure for Parkinson's Disease: The Preference-Based Parkinson's Disease Index (PB-PDI)

Background Parkinson's disease (PD) is a neurodegenerative condition, predominantly affecting older adults. Preference-based measures (PBMs) can be used to make decisions about the cost-utility of different treatments. There are currently no PBMs for health-related quality of life (HRQoL) for PD. A previous study identified important health domains for individuals with PD and developed an item pool from existing measures per domain. The current study aims to contribute to the development of a new disease-specific PBM of HRQoL for PD by reducing the current pool of items according to the preferences of individuals with PD. Methods Fifty-three participants completed a visual analogue scale (VAS) of self-perceived health, the prototype PBM measure, and an item importance rating. To reduce the item pool, the following were calculated: (1) inter-item correlations; (2) impact of each item based on item performance and importance rating; (3) directionality of response options by comparing the VAS scores against each item. Results Participants (male = 54.7%, age = 60.0 ± 10.2) had a median Hoehn and Yahr score of 2.5 (interquartile range = 1). Items supported for inclusion by this analysis were sleep, fatigue, tremor, mood, walking, memory, and dexterity. Items demonstrating a logical decrease in VAS score with each increasing severity level were sleep, memory, tremor, fatigue, and mood. Conclusion This PBM will be critical for informing decisions about the cost-utility of PD treatments, guiding the resource allocation within our healthcare system. Future research will include cognitive debriefing with individuals with PD to refine item response options.
Interacting fermions and N = 2 Chern-Simons-matter theories

: The partition function on the three-sphere of N = 3 Chern-Simons-matter theories can be formulated in terms of an ideal Fermi gas. In this paper we show that, in theories with N = 2 supersymmetry, the partition function corresponds to a gas of interacting fermions in one dimension. The large N limit is the thermodynamic limit of the gas and it can be analyzed with the Hartree and Thomas-Fermi approximations, which lead to the known large N solutions of these models. We use this interacting fermion picture to analyze in detail N = 2 theories with one single node. In the case of theories with no long-range forces we incorporate exchange eﬀects and argue that the partition function is given by an Airy function, as in N = 3 theories. For the theory with g adjoint superﬁelds and long-range forces, the Thomas-Fermi approximation leads to an integral equation which determines the large N , strongly coupled R -charge.
On a conservative concept for output static stabilizability:analysis, consequences, and related problems

This communication is concerned with the problem of stabilization, via output static feedback, of linear time-invariant finite-dimensional systems. A new output static stabilization concept is introduced: output static stabilization in the relaxed sense. This conservative stabilization concept is the result of imposing an additional condition to a set of necessary and sufficient conditions for output static stabilization. This paper is devoted to exhaustively study the introduced new stabilization concept: (I) It is shown that for a particular class of plants, the stabilization problem in the above sense can be cast as a convex programming problem. (II) A full characterization of the class of plants that are stabilizable in the above new sense is presented. Some of the important consequences of that study are as follows: (1) The identification of a class of plants stabilizable, via output static feedback, for which stabilizing feedback matrices can be (almost) expressed in analytic closed form. (2) It is shown that the introduced new conservative stabilization concept is much more significant that it appears; the general problem of output static stabilization can be transformed into the stabilization problem in this new conservative sense. (3) A relationship between output static stabilizability and the LQR problem is proved. (4) A novel generalization of the famous Lyapunov's theorem is presented. Convex necessary and sufficient conditions, for joint stabilization (of multiple plants) in the above sense and, for decentralized stabilization in the above sense, are also presented. Numerical examples illustrate some of the results.
Application of herbs and their derivatives in broiler chickens: a review

SUMMARY Botanical medicine is an ancient medicine used by human beings for thousands of years. Recently, phytobiotics, which are phytochemical compounds derived from plants, are investigated and used widely in the veterinary field as an alternative feed additive to antibiotic growth promoters. Phytobiotic feed additives can be defined as plants-/herbs-derived products added to the feed in order to improve performance of animals. Phytobiotics include herbs (non-woody and non-persistent plants), spices (with a powerful scent or flavour) and essential oils. These phytobiotics conatin subsequent tens of active principles that are classified into six major bioactive chemicals: phenolic, organosulfur, nitrogen-containing compounds, phytosterols, alkaloids, and carotenoids. Each chemical class of phytobiotics has a mode of action; e.g. phenolic compounds or flavonoids as major active ingredients are identified as potential antimicrobial and antioxidant agents. Therefore, the growth promotion outcome induced by phytobiotic feed additives varies depending on the phytochemical mixture used and their active chemicals as well as their concentrations. This review highlights the mode of actions of various phytobiotics, and their beneficial effects on feed intake, gut health, immune system, blood picture and biochemical indices as well as visceral organs, and subsequently their final outcome as growth promoters in poultry nutrition.
Intra-cervical Foley Balloon Catheter Versus Prostaglandins for the Induction of Labour: A Literature Review

Labour induction involves helping a woman to start her labour, before labour begins on its own, for a vaginal birth with the aid of artificial methods, such as medications or other medical techniques. Labour induction is done in cases where extending the pregnancy can threaten the mother or her baby's health, and delivery should result in better outcomes than continuing the pregnancy. Currently, nearly 25% of babies are born by labour induction in economically developed countries. It is often necessary in certain situations to induce labour by using ripening techniques that not only soften the cervix but also make it thin and dilated. Mechanical or pharmacological approaches are used for the artificial induction of labour. Because research articles evaluating the safety and efficacy of various ripening techniques of the cervix vary in terms of their findings, it remains uncertain as to which is the best way to induce labour. In light of this, to find out the most popular interventions for ripening of the cervix during labour induction, we performed a review of the literature that compares the use of a Foley catheter and prostaglandins (misoprostol and dinoprostone). Our findings show that using misoprostol orally is much better than using it vaginally. Foley catheter proved to be the least effective induction technique, despite the fact that it offers the lowest risk.
Using Reinforcement Learning to Reduce Energy Consumption of Ultra-Dense Networks With 5G Use Cases Requirements

In mobile networks, 5G Ultra-Dense Networks (UDNs) have emerged as they effectively increase the network capacity due to cell splitting and densification. A Base Station (BS) is a fixed transceiver that is the main communication point for one or more wireless mobile client devices. As UDNs are densely deployed, the number of BSs and communication links is dense, raising concerns about resource management with regard to energy efficiency, since BSs consume much of the total cost of energy in a cellular network. It is expected that 6G next-generation mobile networks will include technologies such as artificial intelligence as a service and focus on energy efficiency. Using machine learning it is possible to optimize energy consumption with cognitive management of dormant, inactive and active states of network elements. Reinforcement learning enables policies that allow sleep mode techniques to gradually deactivate or activate components of BSs and decrease BS energy consumption. In this work, a sleep mode management based on State Action Reward State Action (SARSA) is proposed, which allows the use of specific metrics to find the best tradeoff between energy reduction and Quality of Service (QoS) constraints. The results of the simulations show that, depending on the target of the 5G use case, in low traffic load scenarios and when a reduction in energy consumption is preferred over QoS, it is possible to achieve energy savings up to 80% with 50 ms latency, 75% with 20 ms and 10 ms latencies and 20% with 1 ms latency. If the QoS is preferred, then the energy savings reach a maximum of 5% with minimal impact in terms of latency.
K-Best Sphere Decoding of Lattice Codes Based on CRC Code

This work proposes a CRC-aided K-best sphere decoding scheme to improve the performance of lattice codes. The generator of the lattice is designed as to be an upper triangular, which is naturally suited for sphere decoding. When the K is sufficiently large, the naïve K-best sphere decoding can approach the lower bound of block error rate (BLER) of maximum likelihood (ML). Therefore, the proposed scheme can outperforms the naïve K-best sphere decoding with the assistance of CRC code.
In-Network Placement of Reusable Computing Tasks in an SDN-Based Network Edge

Edge computing is aimed to support compute-intensive data-hungry interactive applications which can hardly run on resource-constrained consumer devices and may suffer from running in the cloud due to the long data transfer delay. The edge network nodes’ heterogeneous and limited (compared to the cloud) capabilities make the computing task placement a challenge. In this paper, we propose a novel in-network task placement strategy aimed at minimizing the edge network resources usage. The proposal specifically accounts for time-limited reusable computing tasks, i.e., tasks whose output can be cached to serve requests from different consumers for a certain time. Caching such results, during their time validity, achieves the twofold benefit of reducing the service provisioning time and improving the edge resource utilization, by avoiding redundant computations and data exchange. The devised strategy is implemented as a network application of a Software-defined Networking Controller in charge of overseeing the edge domain. We formulate the optimal task placement through an integer linear programming problem, and we define an efficient heuristic algorithm that well approximates the solution achieved through a standard optimal solver. Achieved results show that the proposal successfully meets the targeted objectives in a wide variety of simulated scenarios, by outperforming benchmark solutions.