Miracle-dz/UniFAR-FTUs huggingface dataset:
On the realization of VANET using named data networking: On improvement of VANET using NDN‐based routing, caching, and security

Named data networking (NDN) presents a huge opportunity to tackle some of the unsolved issues of IP‐based vehicular ad hoc networks (VANET). The core characteristics of NDN such as the name‐based routing, in‐network caching, and built‐in data security provide better management of VANET proprieties (e.g., the high mobility, link intermittency, and dynamic topology). This study aims at providing a clear view of the state‐of‐the‐art on the developments in place, in order to leverage the characteristics of NDN in VANET. We resort to a systematic literature review (SLR) to perform a reproducible study, gathering the proposed solutions and summarizing the main open challenges on implementing NDN‐based VANET. There exist several related studies, but they are more focused on other topics such as forwarding. This work specifically restricts the focus on VANET improvements by NDN‐based routing (not forwarding), caching, and security. The surveyed solution herein presented is performed between 2010 and 2021. The results show that proposals on the selected topics for NDN‐based VANET are recent (mainly from 2016 to 2021). Among them, caching is the most investigated topic. Finally, the main findings and the possible roadmaps for further development are highlighted.
Mismatch repair proteins expression and tumor-infiltrating T-cells in colorectal cancer

Microsatellite instability (MSI) and tumor mutational burden (TMB) are indicators of the tumor mutational load, which can lead to immune cell recruitment. By contrast, the number of tumor-infiltrating T cells (TITs) is indicative of the host immune response to tumor cells. The present study evaluated if the expression of mismatch repair (MMR) proteins can be used as a precise tool to assess immunogenicity in the tumor microenvironment. A total of 73 colorectal cancer cases were enrolled in the present study. MMR protein expression was assessed using four-antibodies immunohistochemistry (IHC) targeting MLH1, MSH2, MSH6 and PMS2. TIT was assessed through IHC by counting CD3+ and CD8+ cells in tumor. The enrolled cases were classified into four groups according to MMR and TIT status i) Mismatch repair-proficient (pMMR) and a high number of TITs (pMMR/TIT-H); ii) pMMR and a low number of TITs (pMMR/TIT-L); iii) mismatch repair-deficient (dMMR) and TIT-H (dMMR/TIT-H); and iv) dMMR/TIT-L]. The present study evaluated the clinicopathological characteristics of the four groups, in addition to the difference of TMB. TMB analysis was counted the number of the somatic mutations through multi-genes panel using next-generation sequencing. Clinicopathological characteristics, including age, sex, pathological depth of invasion and lymph node metastasis, were not found to be statistically different between dMMR/TIT-H and dMMR/TIT-L groups. Tumors among pMMR/TIT-H group were associated with poorly differentiation compared with those in pMMR/TIT-L group (P=0.025). The median TMB among the dMMR/TIT-H group was the highest in four groups but the median TMB was <10 muts/Mb in dMMR/TIT-L, pMMR/TIT-H and pMMR/TIT-L groups, respectively. However, one tumor in the pMMR/TIT-H group showed high TMB. The present findings suggest that assessing MMR status alone may not be sufficient to precisely evaluate the antitumor immune response in the tumor microenvironment.
Lectures on Quantum Computation, Quantum Error Correcting Codes And Information Theory

Preface These notes were prepared by Amitava Bhattacharya on a course of lectures I gave at the Tata Institute of Fundamental Research (Mumbai) in the months of April 2001 and February 2002. I am grateful to my colleagues at the TIFR, in general, and Professor Parimala Raman in particular, for providing me a receptive and enthusiastic audience and showering on me their warm hospitality. I thank Professor Jaikumar for his valuable criticism and insight and several fruitful conversations in enhancing my understanding of the subject. Finally, I express my warm appreciation of the tremendous effort put in by Amitava Bhattacharya for the preparation of these notes and their L A T E X files.
Intelligent Massive MIMO Systems for Beyond 5G Networks: An Overview and Future Trends

Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the potential of challenging large-scale problems in conventional massive multiple-input-multiple-output (CM-MIMO) systems. This introduces the concept of intelligent massive MIMO (I-mMIMO) systems. Due to the surge of application of different ML techniques in the enhancement of mMIMO systems for existing and emerging use cases beyond fifth-generation (B5G) networks, this article aims to provide an overview of the different aspects of the I-mMIMO systems. First, the characteristics and challenges of the CM-MIMO have been identified. Secondly, the most recent efforts aimed at applying ML to a different aspect of CM-MIMO systems are presented. Thirdly, the deployment of I-mMIMO and efforts towards standardization are discussed. Lastly, the future trends of I-mMIMO-enabled application systems are presented. The aim of this paper is to assist the readers to understand different ML approaches in CM-MIMO systems, explore some of the advantages and disadvantages, identify some of the open issues, and motivate the readers toward future trends.
Virulence Genotyping and Multidrug Resistance Pattern of Escherichia coli Isolated From Community-Acquired and Hospital-Acquired Urinary Tract Infections

Introduction Uropathogenic Escherichia coli(UPEC) strains consist of a plethora of putative virulence factors (VFs), which help them to establish infection in the urinary tract. We compared genotypic profiles of Escherichia coli (E. coli) strains associated with community-acquired (CA) urinary tract infection (UTI; n=100) and hospital-acquired (HA) UTI (n=50) in the present study in order to identify specific virulence determinants, if any, associated with either form of UTI and its association with antibiotic resistance pattern of the isolates. Materials and methods E. coli strains were analyzed for antimicrobial susceptibility patterns, phylogroups, and 10 putative virulence-associated genes. The bacterial culture and identification were done using standard conventional methods. Tests for antimicrobial susceptibility and phenotypic detection for extende- spectrum beta-lactamases (ESBL) were done by using the Kirby Bauer disc diffusion method, and results were interpreted as per Clinical & Laboratory Standards Institute (CLSI) guidelines. The phylotype (A, B1, B2, and D) of each E. coli isolate was determined by a triplex polymerase chain reaction (PCR) based phylotyping method. They were further analyzed for the presence of 10 putative virulence genes (VGs), including adhesins papA (P fimbrial structural subunit), papG alleles I, II (P fimbrial adhesin variants), fimH (type 1 fimbriae), toxins hlyA (hemolysin) siderophores chuA (heme-binding protein); yfcV (encodes a major subunit of a putative chaperone-usher fimbria) capsule synthesis specific for group II (K1, K5, K12, etc.) kpsMII; serum resistance‐associated traT, and upaH by multiplex PCR. Results HA E. coli isolates were significantly more drug-resistant than CA isolates; carbapenem (80% vs. 16%), ceftazidime (92% vs. 63%). The majority (52%) of E.coli isolates associated with HA UTI belong to commensal phylogroup A and B1, whereas the majority (66%) in CA were from pathotypic phylogroups, i.e., B2 & D. Most of VFs were frequently present amongst CA group except for traT and yfc, kpsMTII, hlyA, chuA, and upaH were significantly associated with CA E.coli isolates while yfc was significantly present in HA E.coli isolates. Though adhesin genes such as papA, papGI, papGII, fimH were frequently found in the CA group, they were not significantly associated. The average virulence score was higher for CA UTI isolates (4.25) than for the HA strains (3.9). Multidrug resistance (MDR) was present in every HA E.coli isolate, and fimH, traT, and yfc genes showed significant association with MDR strains. Conclusion On detailed analysis, we found that HA E. coli isolates had a high frequency of MDR and comparatively reduced VFs content. Thus, it can be assumed that a strain with lesser virulence is able to cause HA UTIs, as compared to CA UTIs, which probably indicates that the host’s immune status/general condition can be an important determinant in acquiring infection rather than virulence potential of the pathogen alone.
cyy-287, a novel pyrimidine-2,4-diamine derivative, inhibits tumor growth of EGFR-driven non-small cell lung cancer via the ERK pathway

In recent decades, EGFR-targeted tyrosine kinase inhibitors (TKIs) have been proven to be an effective therapy for EGFR-mutant non-small cell lung cancer (NSCLC). However, resistance to EGFR-TKIs limits their clinical application. In the present study, we investigate the antitumor effect and underlying mechanism of a novel pyrimidine-2,4-diamine derivative, cyy-287, in NSCLC. We find that cyy-287 has a high affinity for lung tissue and inhibits the proliferation of NSCLC cells. Interestingly, the significant suppression of migration and induction of apoptosis by cyy-287 are only observed in EGFR-driven but not in EGFR-wild-type (wt) cells. According to the RNA sequencing and KEGG enrichment analysis results, cyy-287 markedly inhibits the MAPK pathway in EGFR-driven PC9 cells, and western blot analysis results further indicate that cyy-287 selectively blocks the ERK pathway in EGFR-driven cells. Meanwhile, apoptosis induced by cyy-287 could be partially reversed by ERK pathway inhibition. Further experiment indicates that cyy-287 inhibits the EGFR pathway in both EGFR-driven and EGFR-overexpressing cells. Interestingly, it only induces apoptosis in EGFR-driven cells, not in EGFR-overexpressing cells. The growth of EGFR-driven cells is suppressed by cyy-287 in vivo, with fewer side effects. Our results suggest that cyy-287 may be a potential therapeutic drug with promising antitumor effects against NSCLC.
Conteo de modelos en la clase sintáctica 2μ-3MON

The counting model problem in Boolean formulas is #P-complete, i.e., there is no known deterministic algorithm in the classical computability model (Turing machine) that makes this count in polynomial time. The difficulty persists even imposing more restrictive conditions on the syntactic classes of Boolean formulas. In this paper we present a treatable family within the syntactical class 2 -3MON. The identification of this family is done by using the hypergraph associated with simple structures such as chains and cycles. Then, matrix operators acting over these structures are identified; these operators lead to efficient algorithms that perform the model counting on the identified family in linear time for the number of clauses in the instantiated formula; unlike hypergraphic invariant based methods (such as tree width), which perform the count in cubic time. 1. Introducci´ on
Analytical Approaches in Official Food Safety Control: An LC-Orbitrap-HRMS Screening Method for the Multiresidue Determination of Antibiotics in Cow, Sheep, and Goat Milk

The presence of unauthorized substances, such as residues of veterinary medicines or chemical contaminants, in food can represent a possible health concern. For this reason, a complete legislative framework has been established in the European Union (EU), which defines the maximum limits allowed in food and carries out surveillance programs to control the presence of these substances. Official food control laboratories, in order to ensure a high level of consumer protection, must respond to the challenge of improving and harmonizing the performance of the analytical methods used for the analysis of residues of authorized, unauthorized, or prohibited pharmacologically active substances. Laboratories must also consider the state of the art of the analytical methodologies and the performance requirements of current legislation. The aim of this work was to develop a multiresidue method for the determination of antibiotics in milk, compliant with the criteria and procedures established by Commission Implementing Regulation (EU) 2021/808. The method uses an LC-Orbitrap-HRMS for the determination of 57 molecules of antibiotic and active antibacterial substances belonging to different chemical classes (beta-lactams, tetracyclines, sulfonamides, quinolones, pleuromutilins, macrolides, and lincosamides) in bovine, ovine, and goat milk samples. It provides a simple and quick sample pretreatment and a subsequent identification phase of analytes, at concentrations equal to or lower than the maximum residual limit (MRL), in compliance with Commission Regulation (EU) 2010/37. The validation parameters: selectivity, stability, applicability, and detection capability (ccβ), are in agreement with the requirements of Commission Implementing Regulation (EU) 2021/808 and demonstrated the effectiveness of the method in detecting veterinary drug residues at the target screening concentration (at the MRL level or below), with a false positive rate of less than 5%. This method represents an effective solution for detecting antibiotics in milk, which can be successfully applied in routine analyses for official food control plans.
Hydrodynamic instability growth of three-dimensional, “native-roughness” modulations in x-ray driven, spherical implosions at the National Ignition Facility

Hydrodynamic instability growth experiments with three-dimensional (3-D) surface-roughness modulations were performed on plastic (CH) shell spherical implosions at the National Ignition Facility (NIF) [E. M. Campbell, R. Cauble, and B. A. Remington, AIP Conf. Proc. 429, 3 (1998)]. The initial capsule outer-surface roughness was similar to the standard specifications (“native roughness”) used in a majority of implosions on NIF. The experiments included instability growth measurements of the perturbations seeded by the thin membranes (or tents) used to hold the capsules inside the hohlraums. In addition, initial modulations included two divots used as spatial fiducials to determine the convergence in the experiments and to check the accuracy of 3D simulations in calculating growth of known initial perturbations. The instability growth measurements were performed using x-ray, through-foil radiography of one side of the imploding shell, based on time-resolved pinhole imaging. Averaging over 30 similar images .
Differential Weight Quantization for Multi-Model Compression

Low bit-width quantization can effectively reduce the storage and computational costs of deep neural networks. Existing quantization methods are commonly designed for single model compression. For multi-model compression scenarios, multiple models for the same task or similar tasks need to be compressed simultaneously in multimedia tasks, such as compressing image super-resolution models for different scales and transferring of different models in multimedia. However, single model quantization methods do not consider the correlations among the weights of different models, which limits the further compression for the above multi-model compression scenarios. To sufficiently excavate the potential of compression on multi-model, we propose a novel quantization scheme for multi-model compression, namely differential weight quantization (DWQ), which focuses on the weights increment between the target model and the reference model. Specifically, DWQ is achieved by increment computation, increment quantization and fine-tuning, which utilizes the reference model to guide the subsequent quantization on the target model. Due to the correlations between the weights of different models, the distribution of weights increment is more centralized compared with original weights, which can achieve a higher compression ratio by lower bit representation on weights increment. Moreover, the progressive training method is proposed to accelerate the convergence and reduce quantization loss on the DWQ framework. Extensive experiments validate the effectiveness of DWQ based on weight-sharing and parameterized clipping activation (PACT) quantization technologies on multiple tasks. The proposed framework can achieve 2× compression improvement and reduce 30% computational complexity with comparable performance in the popular multimedia tasks.
Fault Tolerant Multi-Tx/Multi-Rx Inductive Power Transfer System With a Resonator Coil

This article presents a novel multi-transmitter (Tx)/multi-receiver (Rx) inductive power transfer (IPT) system. Compared with the conventional single-Tx/single-Rx systems, multi-Tx/multi-Rx topologies increase reliability and fault tolerance. However, unequal power distribution is challenging in these systems due to coupling differences, which prevents them from operating at rated power or requires overdesigned modules. This study proposes the addition of a middle-stage resonator (MSR) that balances power distribution by separating direct couplings between Tx and Rx coils. Thus, it increases reliability and fault tolerance. Direct couplings between Tx and Rx coils are avoided via the proposed coil structure, which also provides rotational symmetry. Moreover, an analytical method is proposed to avoid bifurcation, which reduces switching losses. Then, the fault tolerance analysis on multi-Tx/multi-Rx systems and optimum selection of module numbers are investigated. Finally, a 1-kW 2Tx/1MSR/4Rx prototype is established to continue operation under single-Tx, single-Rx, and double-Rx open-circuit faults.
Probing the Physics of Gamma-Ray Blazars with Single-Dish Monitoring Data

In the 1990s a comparison of sparse EGRET measurements with single-dish flux density monitoring from the Metsahovi and UMRAO programs established a temporal connection between the onset of flaring at radio band and the occurrence of gamma-ray activity. Correlations between the emergence of new VLBI components from the core, flares in linearly polarized radio flux, and gamma-ray activity in bright EGRET-detected blazars supported a picture in which the gamma-ray and the radio band emission arises in the same shocked region of the jet, with the high energy emission produced via inverse Compton scattering by the synchrotron-emitting electrons in the jet. Quantitative tests of this scenario, however, were hampered by insufficient temporal sampling of the data and the simple nature of the models adopted. The extensive data from Fermi coupled with the wealth of well-sampled radio band data from old as well as new programs such as the F-GAMMA project now permit statistical studies for large numbers of sources, including weak HBLs, and detailed analyses of individual highly-active class members. I summarize progress in understanding the origin of the gamma-ray emission using these new measurements. I focus on three areas: attempts to isolate the physical site of the high energy emission using time delay information; investigation of the emission process using the characteristics of the variability; and quantitative tests of the shock model picture using high-time-sampled multifrequency linear polarization data, VLBP imaging, and new models of propagating oblique relativistic shocks incorporating detailed radiative transfer calculations.
Vaccine-Induced Subcutaneous Granulomas in Goats Reflect Differences in Host–Mycobacterium Interactions between BCG- and Recombinant BCG-Derivative Vaccines

Tuberculous granulomas are highly dynamic structures reflecting the complex host–mycobacterium interactions. The objective of this study was to compare granuloma development at the site of vaccination with BCG and its recombinant derivatives in goats. To characterize the host response, epithelioid cells, multinucleated giant cells (MNGC), T cell subsets, B cells, plasma cells, dendritic cells and mycobacterial antigen were labelled by immunohistochemistry, and lipids and acid-fast bacteria (AFB) were labelled by specific staining. Granulomas with central caseous necrosis developed at the injection site of most goats though lesion size and extent of necrosis differed between vaccine strains. CD4+ T and B cells were more scarce and CD8+ cells were more numerous in granulomas induced by recombinant derivatives compared to their parental BCG strain. Further, the numbers of MNGCs and cells with lipid bodies were markedly lower in groups administered with recombinant BCG strains. Microscopic detection of AFB and mycobacterial antigen was rather frequent in the area of central necrosis, however, the isolation of bacteria in culture was rarely successful. In summary, BCG and its recombinant derivatives induced reproducibly subcutaneous caseous granulomas in goats that can be easily monitored and surgically removed for further studies. The granulomas reflected the genetic modifications of the recombinant BCG-derivatives and are therefore suitable models to compare reactions to different mycobacteria or TB vaccines.
Markov Chain Approach to Probabilistic Guidance for Swarms of Autonomous Agents

Motivated by biological swarms occurring in nature, there is recent interest in developing swarms comprised completely of engineered agents. The main challenge for developing swarm guidance laws compared to earlier formation flying and multi‐vehicle coordination approaches is the sheer number of agents involved. While formation flying applications might involve up to 10 to 20 agents, swarms are desired to contain hundreds to many thousands of agents. In order to deal with the sheer size, the present paper makes a break with past deterministic methods, and considers the swarm as a statistical ensemble for which guidance can be performed from a probabilistic point of view. The probability‐based approach takes advantage of the law of large numbers, and leads to computationally tractable and implementable swarm guidance laws. Agents following a probabilistic guidance algorithm make statistically independent probabilistic decisions based solely on their own state, which ultimately guides the swarm to the desired density distribution in the configuration space. Two different synthesis methods are introduced for designing probabilistic guidance laws. The first is based on the Metropolis‐Hastings (M‐H) algorithm, and the second is based on using linear matrix inequalities (LMIs). The M‐H approach ensures convergent swarm behavior subject to enforced desired motion constraints, while the LMI approach additionally ensures exponential convergence with a prescribed decay rate, and allows minimization of a cost function that reflects fuel expenditure. In addition, both algorithms endow the swarm with the property of self‐repair, and the capability to strictly enforce zero‐probability keep‐out regions. This last property requires a slight generalization of the Perron‐Frobenius theory, and can be very useful in swarm applications that contain regions where no agents are allowed to go. Simulation examples are given to illustrate the methods and demonstrate desired properties of the guided swarm.