Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of BGP Multihomed Link Utilization Effect on Internet Services (http, ftp and email)

internet services and network performance represented in end-to-end delay and jitter are studied with respect to different link utilization. Internet users will access the internet services through simulated internet network contains number of BGP routers and Multihomed links. Both link utilization effect on the different internet services and the inability of BGP to automatically redistribute the traffic over available Multihomed Links will be highlighted.This paper also introduce a simple network design which is very close to the real internet environment and covers internet users section , ISPs section and enterprise section which represents offered internet services hoping that this model give a hand in the BGP and internet services researches. KeywordsMultihomed; HTTP; FTP; Email; OPNET.
Studying anatomy through a problem-based learning approach

Reforming traditional anatomy by linking it to clinical practice has great benefits for learning. The application of anatomical principles in the explanation of clinical signs and therapeutic procedures enhances the motivation of students to learn anatomy. As a result of this reform, problem-based learning (PBL) is a pedagogical method that appeared a few decades ago [1]. It is used not only during pre-doctoral medical studies, but also more and more early in the medical curriculum. In the Faculty of Medicine of Saint-Louis, Senegal, the adaptation of students to this new teaching method is progressively made in anatomy. The introduction of problem-based learning in a curriculum offers teachers and students another approach to anatomical pedagogy [2]. This method offers a more modern approach to the teaching of anatomy, more fulfilling for the student because it is directly related to clinical approach.
A rigorous measure of genome-wide genetic shuffling that takes into account crossover positions and Mendel’s second law

Comparative studies in evolutionary genetics rely critically on evaluation of the total amount of genetic shuffling that occurs during gamete production. However, such studies have been ham-pered by the fact that there has been no direct measure of this quantity. Existing measures consider crossing over by simply counting the average number of crossovers per meiosis. This is qualitatively inadequate because the positions of crossovers along a chromosome are also critical: a crossover towards the middle of a chromosome causes more shuffling than a crossover towards the tip. More-over, traditional measures fail to consider shuffling from independent assortment of homologous chromosomes (Mendel’s second law). Here, we present a rigorous measure of genome-wide shuffling that does not suffer from these limitations. We define the parameter r̅ as the probability that the alleles at two randomly chosen loci will be shuffled in the production of a gamete. This measure can be decomposed into separate contributions from crossover number and position and from independent assortment. Intrinsic implications of this metric include the fact that r̅ is larger when crossovers are more evenly spaced, which suggests a novel selective advantage of crossover interference. Utilization of r̅ is enabled by powerful emergent methods for determining crossover positions, either cytologically or by DNA sequencing. Application of our analysis to such data from human male and female reveals that: (i) r̅ in humans is close to its maximum possible value of 1/2, (ii) this high level of shuffling is due almost entirely to independent assortment, whose contribution is ~30 times greater than that of crossovers.
OMICS, Oral Cancer Molecular Landscapes, and Clinical Practice

Abstract Molecular pathogenesis of oral cancers continues to be researched by omics systems science biotechnologies. Oral cancers rank as the 13th most common cancer globally. Notably, the burden of oral cancers from the Asian continent is 56.21%, with 26% of the burden contributed by India. Despite easy accessibility of the oral cavity and hence early detection of oral cancers, majority are diagnosed in advanced stages in the Asian countries. Innovation in oral cancer diagnostics, as well as theranostics for precision medicine, would aid their early diagnosis, prognosis, and treatment, not to mention discovery of novel molecular targets for drug development. This expert review offers an analysis of oral cancer biomarkers, including somatic mutations, deregulated expression, epigenetic regulation, and genomic variants associated with oral cancer. We also discuss the implications of the current and emerging oral cancer biomarkers with a view to clinical practice, global health, and make suggestions for the.
One-bit Counts between Unique and Sticky Technical Report 516 July 1998

Stoye’s one-bit reference tagging scheme can be extended to local counts of two or more via two strategies. The first, suited to pure register transactions, is a cache of referents to two shared references. The analog of Deutsch’s and Bobrow’s multiple-reference table, this cache is sufficient to manage small counts across successive assignment statements. Thus, accurate reference counts above one can be tracked for short intervals, like those bridging one function’s environment to its successor’s. The second, motivated by runtime stacks that duplicate references, avoids counting any references from the stack. It requires a local pointer-inversion protocol in the mutator, but one still local to the referent and the stack frame. Thus, an accurate reference count of one can be maintained regardless of references from the recursion stack.
Robustness of early warning signals for catastrophic and non-catastrophic transitions

Early warning signals (EWS) are statistical indicators that a rapid regime shift may be forthcoming. Their development has given ecologists hope of predicting rapid regime shifts before they occur. Accurate predictions, however, rely on the signals being appropriate to the system in question. Most of the EWS commonly applied in ecology have been studied in the context of one specific type of regime shift (the type brought on by a saddle-node bifurcation, at which one stable equilibrium point collides with an unstable equilibrium and disappears) under one particular perturbation scheme (temporally uncorrelated noise that perturbs the net population growth rate in a density independent way). Whether and when these EWS can be applied to other ecological situations remains relatively unknown, and certainly underappreciated. We study a range of models with different types of dynamical transitions (including rapid regime shifts) and several perturbation schemes (density-dependent uncorrelated or temporally-correlated noise) and test the ability of EWS to warn of an approaching transition. We also test the sensitivity of our results to the amount of available pre-transition data and various decisions that must be made in the analysis (i.e. the rolling window size and smoothing bandwidth used to compute the EWS). We find that EWS generally work well to signal an impending saddle-node bifurcation, regardless of the autocorrelation or intensity of the noise. However, EWS do not reliably appear as expected for other types of transition. EWS were often very sensitive to the length of the pre-transition time series analyzed, and usually less sensitive to other decisions. We conclude that the EWS perform well for saddle-node bifurcation in a range of noise environments, but different methods should be used to predict other types of regime shifts. As a consequence, knowledge of the mechanism behind a possible regime shift is needed before EWS can be used to predict it.
Clingen Cancer Somatic Working Group – standardizing and democratizing access to cancer molecular diagnostic data to drive translational research

A growing number of academic and community clinics are conducting genomic testing to inform treatment decisions for cancer patients (1). In the last 3–5 years, there has been a rapid increase in clinical use of next generation sequencing (NGS) based cancer molecular diagnostic (MolDx) testing (2). The increasing availability and decreasing cost of tumor genomic profiling means that physicians can now make treatment decisions armed with patient-specific genetic information. Accumulating research in the cancer biology field indicates that there is significant potential to improve cancer patient outcomes by effectively leveraging this rich source of genomic data in treatment planning (3). To achieve truly personalized medicine in oncology, it is critical to catalog cancer sequence variants from MolDx testing for their clinical relevance along with treatment information and patient outcomes, and to do so in a way that supports large-scale data aggregation and new hypothesis generation. One critical challenge to encoding variant data is adopting a standard of annotation of those variants that are clinically actionable. Through the NIH-funded Clinical Genome Resource (ClinGen) (4), in collaboration with NLM’s ClinVar database and >50 academic and industry based cancer research organizations, we developed the Minimal Variant Level Data (MVLD) framework to standardize reporting and interpretation of drug associated alterations (5). We are currently involved in collaborative efforts to align the MVLD framework with parallel, complementary sequence variants interpretation clinical guidelines from the Association of Molecular Pathologists (AMP) for clinical labs (6). In order to truly democratize access to MolDx data for care and research needs, these standards must be harmonized to support sharing of clinical cancer variants. Here we describe the processes and methods developed within the ClinGen’s Somatic WG in collaboration with over 60 cancer care and research organizations as well as CLIA-certified, CAP-accredited clinical testing labs to develop standards for cancer variant interpretation and sharing.
A Two-Dimensional Quantizer for Coding of Digital Imagery

A spatial domain image coding method which is computationally straightforward and requires only one pass through the incoming data is presented. The technique is based on approximating a near-optimal three-level uniform quantizer over a spatially local region of the image. This method can maintain single pixel resolution and is therefore applicable to wide bandwidth data. Results of applying this procedure to a variety of images are given, along with comparisons to some other image coding techniques. A variablelength code word version providing increased compression is also developed.
A REVIEW PAPER ON ALGORITHMS USED FOR TEXT CLASSIFICATION

The textual revolution has seen a tremendous change in the availability of online information. Finding information for just about any need has never been more automatic. Text classification (also known as text categorization or topic spotting) is the task of automatically sorting a set of documents into categories from a predefined set. This task has several applications, including automated indexing of scientific articles, filing patents into patent directories, selective dissemination of information to information consumers, automated population of hierarchical catalogues of Web resources, spam filtering, identification of document genre. Automated text classification is attractive because it frees organizations from the need of manually organizing document bases, which can be too expensive, or simply not feasible given the time constraints of the application or the number of documents involved. The accuracy of modern text classification systems rivals that of trained human professionals, thanks to a combination of information retrieval (IR) technology and machine learning (ML) technology. The aim of this paper is to highlight the important algorithms that are employed in text documents classification, while at the same time making awareness of some of the interesting challenges that remain to be solved.
Adaptive rate MIMO system using space-time block mapping

The MIMO system employing multiple antennas at both the transmitter and the receiver increases the spectral efficiency greatly. But the spectral efficiency of MIMO system depends on spatial channel characteristics. So some kind of adaptive transmission is required according to spatial channel conditions. In this paper, we propose adaptive rate MIMO system using space-time block mapping. The rate is controlled by effective number of spatial channels. The effective number of spatial channels is determined from spatial channel characteristics and is integer number from 1 to the minimum number of transmit and receive antennas. By switching the MIMO mode adaptively according to spatial channel conditions, throughput can be maximized.
Effectiveness of model-based clustering in analyzing Plasmodium falciparum RNA-seq time-course data

Background: The genomics and microarray technology played tremendous roles in the amount of biologically useful information on gene expression of thousands of genes to be simultaneously observed. This required various computational methods of analyzing these amounts of data in order to discover information about gene function and regulatory mechanisms. Methods: In this research, we investigated the usefulness of hidden markov models (HMM) as a method of clustering Plasmodium falciparum genes that show similar expression patterns. The Baum-Welch algorithm was used to train the dataset to determine the maximum likelihood estimate of the Model parameters. Cluster validation was conducted by performing a likelihood ratio test. Results: The fitted HMM was able to identify 3 clusters from the dataset and sixteen functional enrichment in the cluster set were found. This method efficiently clustered the genes based on their expression pattern while identifying erythrocyte membrane protein 1 as a prominent and diverse protein in P. falciparum . Conclusion: The ability of HMM to identify 3 clusters with sixteen functional enrichment from the 2000 genes makes this a useful method in functional cluster analysis for P. falciparum
Combinatorial drug discovery in nanoliter droplets

Significance The conventional single-agent approach to therapeutics is challenged by the redundancy and feedback in biological networks. The use of multiple drugs in combination might improve desired functional outcomes while reducing toxicity and overcoming drug resistance. However, the complexity and resources required to test many combinations have slowed discovery efforts. Here, we introduce a screening platform that automatically constructs combinations of drugs from nanoliter-scale droplets, greatly simplifying screening logistics and reducing resource consumption. We applied our platform to discover drug pairs that act synergistically against the model pathogen Escherichia coli. Our platform can be further developed to support many types of phenotypic assays in a variety of disease models. Combinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the sheer scale of combinatorial chemical space. Here, we report a high-throughput system for nanoliter-scale phenotypic screening that formulates a chemical library in nanoliter droplet emulsions and automates the construction of chemical combinations en masse using parallel droplet processing. We applied this system to predict synergy between more than 4,000 investigational and approved drugs and a panel of 10 antibiotics against Escherichia coli, a model gram-negative pathogen. We found a range of drugs not previously indicated for infectious disease that synergize with antibiotics. Our validated hits include drugs that synergize with the antibiotics vancomycin, erythromycin, and novobiocin, which are used against gram-positive bacteria but are not effective by themselves to resolve gram-negative infections.
Fungal fatal attraction: a mechanistic review on targeting liposomal amphotericin B (AmBisome®) to the fungal membrane

Liposomal amphotericin B (AmBisome®) is a lipid-based nanotherapeutic that is used successfully worldwide to treat a broad range of life-threatening invasive fungal infections. In subtropical regions, AmBisome is emerging as the treatment of choice for human parasitic protozoan pathogens such as those from the genus Leishmania. The key to the remarkable efficacy of AmBisome is attributed to its liposome based formulation to deliver a potent drug at high dosage with significantly reduced toxicity in patients with immunocompromised systems. In spite of the rising frequency of AmBisome usage globally, the mechanisms underlying its ability to target to the sites of infection remain largely unknown. This review provides an overview of the current mechanistic understanding of AmBisome, discusses potential challenges and opportunities for the development of clinically effective, refractory resistant antifungal agents.
Resurgence of Human Immunodeficiency Virus and Treponema Pallidum Co-Infection

The noticeable spike in the prevalence of co-infection with human immunodeficiency virus (HIV) and Treponema pallidum (syphilis) has generated renewed interest in the subject. While it has been well-established that HIV infection does exert some effect on the natural history of syphilis, it was not until the recent resurgence in the contraction of syphilis by HIV patients that researchers were able to document the impact that this disease has on the course of the HIV infection. A correct assertion is that there exists a complex interaction between HIV and syphilis and that this interaction remains partly understood. New data, though, have emerged that augment our comprehension of the interaction between syphilis and HIV infection as it applies to the heterosexual population, bi-sexual partners, and men who have sex with men (MSM).
Cell-specific modulation of nuclear pore complexes controls cell cycle entry during asymmetric division

The acquisition of cellular identity is coupled to changes in the nuclear periphery and nuclear pore complexes (NPCs). Whether and how these changes determine cell fate remains unclear. We have uncovered a mechanism regulating NPC acetylation to direct cell fate after asymmetric division in budding yeast. The lysine deacetylase Hos3 associates specifically with daughter cell NPCs during mitosis to delay cell cycle entry (Start). Hos3-dependent deacetylation of nuclear basket and central channel nucleoporins establishes daughter cell-specific nuclear accumulation of the transcriptional repressor Whi5 during anaphase and perinuclear silencing of the CLN2 gene in the following G1 phase. Hos3-dependent coordination of both events restrains Start in daughter but not in mother cells. We propose that deacetylation modulates transport-dependent and - independent functions of NPCs, leading to differential cell cycle progression in mother and daughter cells. Similar mechanisms might regulate NPC functions in specific cell types and/or cell cycle stages in multicellular organisms.
AM ATHEMATICAL MODEL FOR SEMANTIC SIMILARITY MEASURES

Semantic similarity between words, concepts or sets of concepts has been a fundamental theme and widely studied in various areas including natural language processing, document semantic comparison, artificial intelligence, semantic web, semantic web service, and semantic search engines. Several similarity measures have been proposed but they are usually tied to special application domains or information representation of various application domains. In this paper, we present a mathematical model for distance-based semantic similarity estimation in domains that are represented with ontology - an explicit specification of conceptualization of such domains. Based on this model, we construct algorithms to calculate the semantic similarity between two concepts and one between two sets of concepts. The significance of the proposed mathematical model is that it offers a generalization that enables to maintain flexibility and thus supports various computational measures.
Security Studies and Implementation on Power Mobile Application in the Internet plus Environment

Analyze the security risks of traditional power mobile operating system, design and implement a more secure access system and analyze the overall structure and function of the secure access system in detail in the Internet plus environment. The system can process two-way certificate authentication, secure transmission of data, security access control, network isolation and secure data filtering, real-time monitoring and management, and solve the security problem of mobile power operation applications effectively.
Influence of fecal collection conditions and 16S rRNA gene sequencing protocols at two centers on human gut microbiota analysis

Background To optimise fecal sampling and analysis yielding reproducible microbiome data, and gain further insight into sources of its variation, we compared different collection conditions and 16S rRNA gene sequencing protocols in two centers. Fecal samples were collected on three sequential days from six healthy adults and placed in commercial collection tubes (OMNIgeneGut OMR-200) at room temperature or in sterile 5 ml screw-top tubes in a home fridge or home freezer for 6-24 h, before transfer at 4°C to the laboratory and storage at - 80°C within 24 hours. Replicate samples were shipped on dry ice to centers in Australia and the USA for DNA extraction and sequencing of the V4 region of the 16S rRNA gene, using different PCR protocols. Sequences were analysed with the QIIME pipeline and Greengenes database at the Australian center and with an in-house pipeline and SILVA database at the USA center. Results Variation in gut microbiome composition and diversity was dominated by differences between individuals. Minor differences in the abundance of taxa were found between collection-processing methods and day of collection. Larger differences were evident between the two centers, including in the relative abundances of genus Akkermansia, in phylum Verrucomicrobiales, and Bifidobacteria in Actinobacteria. Conclusions Collection with storage and transport at 4°C within 24 h is adequate for 16S rRNA analysis of the gut microbiome. However, variation between sequencing centers suggests that cohort samples should be sequenced by the same method in one center. Differences in handling, shipping and methods of PCR gene amplification and sequence analysis in different centers introduce variation in ways that are not fully understood. These findings are particularly relevant as microbiome studies shift towards larger population-based and multicenter studies.
A frequency-dependent mobilization of heterogeneous pools of synaptic vesicles shapes presynaptic plasticity

The segregation of the readily releasable pool of synaptic vesicles (RRP) in sub-pool which are differentially poised for exocytosis shapes short-term plasticity at depressing synapses. Here, we used in vitro recording and modeling of synaptic activity at the facilitating mice cerebellar granule cell to Purkinje cell synapse to demonstrate the existence of two sub-pools of vesicles in the RRP that can be differentially recruited upon fast changes in the stimulation frequency. We show that upon low-frequency stimulation, a population of fully-releasable vesicles is silenced, leading to full blockage of synaptic transmission. A second population of vesicles, reluctant to release by simple stimuli, is recruited in a millisecond time scale by high-frequency stimulation to support an ultrafast recovery of neurotransmitter release after low-frequency depression. The frequency-dependent mobilization or silencing of sub-pools of vesicles in granule cell terminals should play a major role in the filtering of sensorimotor information in the cerebellum.