TECHNIQUES TO INDICATE LATENCY OF PACKETS IN NETWORK NODES

Applications operating via network communications have long evolved from the use of basic data, as audio and video applications continue to evolve in terms of latency requirements and, as such, the number of differentiated flows (per application) continues to evolve as well. With applications evolving that are utilize low latency packet paths from network, it can be challenging to determine the latency of packets in a network that are associated with latency sensitive applications. This proposal provides techniques through which a new header can be embedded into packets in which the new header can be used to indicate the total-residence-time of a packet in various nodes in a network. The header can be embedded in each packet that is communicated from an origin to an end-node of a network and can indicate how much time the packet has spent in network. The header can be updated on every node by the value of the time the packet spent in each node in the network (i.e., residence time of the packet in a network node)

TECHNIQUES TO INDICATE LATENCY OF PACKETS IN NETWORK NODES

Applications operating via network communications have long evolved from the use of basic data, as audio and video applications continue to evolve in terms of latency requirements and, as such, the number of differentiated flows (per application) continues to evolve as well. With applications evolving that are utilize low latency packet paths from network, it can be challenging to determine the latency of packets in a network that are associated with latency sensitive applications. This proposal provides techniques through which a new header can be embedded into packets in which the new header can be used to indicate the total-residence-time of a packet in various nodes in a network. The header can be embedded in each packet that is communicated from an origin to an end-node of a network and can indicate how much time the packet has spent in network. The header can be updated on every node by the value of the time the packet spent in each node in the network (i.e., residence time of the packet in a network node)

TECHNIQUES TO PROVIDE AUDIT SECURITY STEERING POLICY ENFORCEMENT

Dynamic and selective steering of traffic through a security device can create a certain level of interdependence between the security operations (SecOps) and network operations (NetOps) that traditionally operate as independent teams. For example, any deviation in the strict enforcement of the true traffic steering intent advised/authored by a SecOps team and configured by a NetOps teams on network devices can result in compliance issues and possibly security breaches. This submission proposes novel techniques that allow a SecOps team to independently audit and validate steering enforcement actions configured and managed by a NetOps team in order to ensure compliance with the original traffic steering intent/policies as provided by the SecOps team

Qualitative Insights Tool (QualIT): LLM Enhanced Topic Modeling

Topic modeling is a widely used technique for uncovering thematic structures from large text corpora. However, most topic modeling approaches e.g. Latent Dirichlet Allocation (LDA) struggle to capture nuanced semantics and contextual understanding required to accurately model complex narratives. Recent advancements in this area include methods like BERTopic, which have demonstrated significantly improved topic coherence and thus established a new standard for benchmarking. In this paper, we present a novel approach, the Qualitative Insights Tool (QualIT) that integrates large language models (LLMs) with existing clustering-based topic modeling approaches. Our method leverages the deep contextual understanding and powerful language generation capabilities of LLMs to enrich the topic modeling process using clustering. We evaluate our approach on a large corpus of news articles and demonstrate substantial improvements in topic coherence and topic diversity compared to baseline topic modeling techniques. On the 20 ground-truth topics, our method shows 70% topic coherence (vs 65% & 57% benchmarks) and 95.5% topic diversity (vs 85% & 72% benchmarks). Our findings suggest that the integration of LLMs can unlock new opportunities for topic modeling of dynamic and complex text data, as is common in talent management research contexts.6 pages, 4 tables, 1 figur

Detection of anti-3AB3 non-structural protein antibodies in foot-and-mouth disease virus vaccinated buffaloes at a semi-organized farm of Madhya Pradesh in India

Foot-and-mouth disease (FMD), one of the most important viral diseases of cloven-hoofed animals in India, is caused by FMD virus (FMDV) which belongs to Aphthovirus in the family Picornaviridae. There are three serotypes of FMDV (O, A and Asia 1) circulating amongst the livestock population of India. FMD is characterized by the formation of vesicles especially over the tongue and in between the interdigital space. FMD-affected animals with tongue lesions are reluctant to feed and subsequently yield less milk as well as affected animals never regain their production status causing huge economic losses to the animal owners. In the present study, random whole blood samples from FMD-vaccinated 38 adult buffaloes were collected in sterile containers of a semi-organized buffalo farm of Madhya Pradesh in India. Purified FMD vaccines only elicit antibodies (that are protective) against structural proteins of FMDV while natural FMDV infection invokes antibodies against both structural and non-structural proteins. Serum samples were employed in recombinant 3AB3 non-structural protein-based enzyme-linked immunosorbent assay (3AB3 NSP-ELISA kit provided by ICAR-Directorate of FMD, Mukteshwar) for differentiation of FMD-infected and vaccinated animals (DIVA). A total of 10.53% (4/38) serum samples tested positive in DIVA. Largely the vaccinated animals remained protected as no clinical signs of the disease were observed reiterating the importance of regular FMDV vaccination in animals at semi-organized dairy farms

FACTORS INFLUENCING ADHERENCE TO IMATINIB IN INDIAN CHRONIC MYELOID LEUKEMIA PATIENTS: A CROSS-SECTIONAL STUDY

Adherence to imatinib(IM) is of utmost importance in patients with chronic myeloid leukemia(CML) to maximise treatment effectiveness. The main objective is to measure adherence to    IM & to evaluate individual patient characteristics, personal, treatment related &                    psychological factors influencing adherence behaviour. Hundred patients  receiving IM were analysed for adherence behaviour using 9 item Morisky Medication Adherence Scale              (9-MMAS) . Various factors were assessed for their impact on adherence behaviour.  These   factors were age, gender, duration of treatment, frequency & dosing of treatment, use  of        tobacco & alcohol, educational qualification,employment status,monthly  income, side effects, financial assistance in treatment, social support, knowledge about medicine & disease,         concomitant drug burden, polypharmacy, physician patient interaction, patient  educational    sessions & prevalence of depression. Seventy five percent of patients were found to be           adherent. On univariate analysis, prevalence of depression (p<0.000001), moderate severe     depression (p<0.000001), concomitant drug burden (p=0.036) & monthly income (p=0.015) were found to be significantly influencing adherence. The final multivariate model retained   prevalence of depression with OR= 10.367  (95% CI, 3.112- 34.538) as independent predictor of adherence to therapy. This study suggests that identification & treatment of depression among CML patients may further enhance adherence to IM therapy. Keywords: Chronic Myeloid Leukemia, Adherence, Imatinib, Nine Item Morisky Medication Adherence Scale, Patient Health Questionnaire -9

Measurements of the pp → ZZ production cross section and the Z → 4ℓ branching fraction, and constraints on anomalous triple gauge couplings at √s = 13 TeV

Four-lepton production in proton-proton collisions, pp -> (Z/gamma*)(Z/gamma*) -> 4l, where l = e or mu, is studied at a center-of-mass energy of 13 TeV with the CMS detector at the LHC. The data sample corresponds to an integrated luminosity of 35.9 fb(-1). The ZZ production cross section, sigma(pp -> ZZ) = 17.2 +/- 0.5 (stat) +/- 0.7 (syst) +/- 0.4 (theo) +/- 0.4 (lumi) pb, measured using events with two opposite-sign, same-flavor lepton pairs produced in the mass region 60 4l) = 4.83(-0.22)(+0.23) (stat)(-0.29)(+0.32) (syst) +/- 0.08 (theo) +/- 0.12(lumi) x 10(-6) for events with a four-lepton invariant mass in the range 80 4GeV for all opposite-sign, same-flavor lepton pairs. The results agree with standard model predictions. The invariant mass distribution of the four-lepton system is used to set limits on anomalous ZZZ and ZZ. couplings at 95% confidence level: -0.0012 < f(4)(Z) < 0.0010, -0.0010 < f(5)(Z) < 0.0013, -0.0012 < f(4)(gamma) < 0.0013, -0.0012 < f(5)(gamma) < 0.0013

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Determination of the strong coupling and its running from measurements of inclusive jet production

The value of the strong coupling S is determined in a comprehensive analysis at next-to-next-to-leading order accuracy in quantum chromodynamics. The analysis uses double-differential cross section measurements from the CMS Collaboration at the CERN LHC of inclusive jet production in proton-proton collisions at centre-of- mass energies of 2.76, 7, 8, and 13 TeV, combined with inclusive deep-inelastic data from HERA. The value $_S$($_Z$ ) = 0.1176 $^{+0.0014}_{-0.0016}$ is obtained at the scale of the Z boson mass. By using the measurements in different intervals of jet transverse momentum, the running of $_S$ is probed for energies between 100 and 1600 GeV