1,721,143 research outputs found
Analysis and Optimal Management of Mobile Networks Towards Pervasive Intelligence
Full text linkQuesta tesi indaga le tecniche di machine learning come potenti strumenti per l'analisi e la gestione ottima delle reti radiomobili per ottenere l’Intelligenza Pervasiva.
In questo contesto, descrive soluzioni recenti progettate per affrontare tre problemi diversi, ma correlati.
In primo luogo, dopo aver adattato una metodologia di unsupervised learning per caratterizzare i pattern di utilizzo delle risorse radio, un modello di multi-task learning, eseguito direttamente ai bordi della rete, è ideato per eseguire il data mining dal canale di controllo di una rete radiomobile operativa.
Due configurazioni di reti neurali, basate su autoencoder Undercomplete o Sequence to Sequence, vengono sfruttate per ottenere rappresentazioni di feature comuni dei profili di traffico.
In seguito, i softmax e fully-connected layer vengono utilizzati rispettivamente per anticipare le informazioni sul tipo di traffico da servire e il pattern di utilizzo delle risorse radio richiesto da ciascun servizio durante la sua esecuzione.
Inoltre, viene sfruttato un approccio Software-Defined Networking per monitorare la mobilità degli utenti.
Di conseguenza, la predizione sia della distribuzione degli utenti tra le celle che delle risorse di comunicazione e di computazione richieste su diversi orizzonti temporali futuri viene eseguita attraverso un'architettura Convolutional Long Short-Term Memory.
Queste informazioni vengono utilizzate per eseguire in anticipo l'allocazione e la distribuzione delle richieste degli utenti tramite Dynamic Programming.
Infine, viene proposto uno schema Tenant-driven di slicing enforcement nella rete di accesso radio basato sull'Intelligenza Pervasiva per evitare l'over-provisioning delle risorse radio risparmiando la banda (ovvero, il paradigma Pay for What You Get).
L’Infrastructure Provider utilizza un autoencoder convoluzionale per comprimere le informazioni sulle risorse di rete e sulla connettività e le condivide con i Tenant.
A sua volta, ogni Tenant implementa un algoritmo Deep Deterministic Policy Gradient per adattare dinamicamente le richieste di banda in base alle esigenze dei propri utenti.
I risultati di questo algoritmo vengono quindi utilizzati dall’Infrastructure Provider per applicare efficacemente lo slicing della rete.
L'indagine in scenari reali e il confronto con approcci convenzionali adottati per l'analisi e la gestione ottima delle reti radiomobili dimostrano l'efficacia delle soluzioni proposte basate sul machine learning. In termini di applicabilità, le metodologie progettate sono anche in linea con l'evoluzione delle reti radiomobili, in cui l'Intelligenza Artificiale sarà integrata in modo nativo e pervasivo per consentire la piena automazione della rete.This thesis investigates machine learning techniques as powerful tools for the analysis and the optimal management of mobile networks towards Pervasive Intelligence.
In this context, it describes recent solutions conceived for addressing three different, but related, issues.
Firstly, after tailoring an unsupervised learning methodology to characterize radio resource utilization patterns, a Multi-Task Learning model, running directly at the edge of the network, is conceived to perform data mining from the control channel of an operative mobile network.
Two configurations of neural networks, based on Undercomplete or Sequence to Sequence autoencoders, are exploited to obtain common feature representations of traffic profiles.
Then, softmax and fully-connected layers are used to anticipate information on the type of traffic to be served and the radio resource utilization pattern requested by each service during its execution, respectively.
Moreover, a Software-Defined Networking approach is exploited to monitor users’ mobility.
Consequently, the prediction of both the distribution of users among cells and the communication and computational resources they request over different look-ahead horizons is performed through a Convolutional Long Short-Term Memory architecture.
This information is used to perform anticipatory allocation and distribution of users' requests via Dynamic Programming.
Hence, a Tenant-driven Radio Access Network slicing enforcement scheme based on Pervasive Intelligence is proposed to avoid the radio resources over-provisioning while saving bandwidth (i.e., the Pay for What You Get paradigm).
The Infrastructure Provider exploits a convolutional autoencoder to compress the information on network resources and connectivity and share it with the Tenants.
In turn, each Tenant implements a Deep Deterministic Policy Gradient algorithm to dynamically adapt bandwidth requests according to its own users' requirements.
The outcomes of this algorithm are then used by the Infrastructure Provider to effectively enforce network slicing.
The investigation in real scenarios and the comparison against conventional approaches adopted for the analysis and the optimal management of mobile networks demonstrate the effectiveness of the proposed machine learning-based solutions. In terms of applicability, the conceived methodologies are also in line with the evolution of mobile networks, where Artificial Intelligence will be natively and pervasively integrated for enabling full network automation
Significance of clustered tumor suppressor genes in cancer
No full textEvaluation of: Xue W, Kitzing T, Roessler S et al. A cluster of cooperating tumor-suppressor gene candidates in chromosomal deletions. Proc. Natl Acad. Sci. USA 109, 8212-8217 (2012). The two-hit model is a well-known mechanism for the inactivation of tumor suppressor genes in cancer and it has been assumed that chromosomal deletions are the second inactivating event. Large deletions are frequently found in cancer and can lead to the haploinsufficiency of the loci mapped to the deleted region. The study by Xue et al. demonstrated that hemizygous 8p deletions can attenuate the activity of multiple genes that control growth and promote tumorigenesis, and showed that the effect of large 8p deletions on tumor phenotype goes beyond the effects of the individual genes as the characteristics of a tumor are also influenced by the additive and/or combined effect of the haploinsufficiency of multiple genes. These convincing findings, demonstrating that the hemizygosity of a cluster of genes negatively regulates proliferation and promotes tumor growth, have opened up new study perspectives aimed at characterizing the genomic organization of this new class of tumor suppressor genes and their role in tumorigenesis
The role of imprinted genes in fetal growth
No full textGenomic imprinting is the phenomenon by which one of the two alleles of a subset of genes is preferentially expressed according to its parental origin. This pattern of inheritance is different from the more frequent mode of Mendelian inheritance, which is not influenced by the parental origin of the allele. The idea that imprinted genes can affect fetal growth is becoming increasingly intriguing as it has been shown that most imprinted genes are expressed in the placenta and some play a role in regulating the interactions between its fetal and maternal interfaces. This article considers genomic imprinting by reviewing recent findings of alterations in fetal growth related to different types of genetic changes affecting the expression of imprinted genes. Among the genetic anomalies, the uniparental disomy (UPD) defines the inheritance of both homologous chromosomes from only one parent. UPDs of a number of chromosomes have been described in association with effects on the phenotype. We reviewed cases of UPD reported till now with particular reference to those associated to growth alterations
Epigenetic alterations in cancer and personalized cancer treatment
No full textBased on the pivotal importance of epigenetics for transcription regulation, it is not surprising that cancer is characterized by several epigenetic abnormalities. Conversely to genetic alterations, epigenetic changes are not permanent, thus represent opportunities for therapeutic strategies designed to reverse transcriptional abnormalities, and cancer is the first disease in which epigenetic therapies with chromatin remodeling agents were introduced. The role of miRNAs in gene regulation supports their potential as innovative therapeutic strategy. Recent evidences have proven that the environment can profoundly influence the epigenome: diet, smoking and alcohol consumption can negatively impact the expression profile. Given the plasticity of epigenetic marks, it is challenging the idea that the epigenetic alterations are 'druggable' sites using specific food components
On the exploitation of user aggregation strategies in heterogeneous wireless networks
No full textIn this paper we discuss the exploitation of aggregated mobility patterns and physical proximity of nodes in a so-called ambient network, i.e., a wireless network with heterogeneous nodes and access techniques. We advocate to use the knowledge about node movements and geographical positions to create routing groups of adjacent nodes, which might be beneficial in order to decrease signaling overhead and increase transmission efficiency. Basically, routing groups (RGs) consist of aggregated logical structures which are built and maintained at the application layer. Their aim is to decrease the signaling overhead between group of nodes and access points and, at the same time, to improve connectivity by exploiting technology diversity and relaying techniques. On this matter, we describe a validation through simulation of a previously developed analytical work which is useful to evaluate the effectiveness of RG structures. Finally, we show the validity of the RG approach in terms of throughput and connectivity performance
Beckwith–Wiedemann and IMAGe syndromes : two very different diseases caused by mutations on the same gene
Full text linkGenomic imprinting is an epigenetically regulated mechanism leading to parental-origin allele-specific expression. Beckwith–Wiedemann syndrome (BWS) is an imprinting disease related to 11p15.5 genetic and epigenetic alterations, among them loss-of-function CDKN1C mutations. Intriguing is that CDKN1C gain-of-function variations were recently found in patients with IMAGe syndrome (intrauterine growth restriction, metaphyseal dysplasia, congenital adrenal hypoplasia, and genital anomalies). BWS and IMAGe share an imprinted mode of inheritance; familial analysis demonstrated the presence of the phenotype exclusively when the mutant CDKN1C allele is inherited from the mother. Interestingly, both IMAGe and BWS are characterized by growth disturbances, although with opposite clinical phenotypes; IMAGe patients display growth restriction whereas BWS patients display overgrowth. CDKN1C codifies for CDKN1C/KIP2, a nuclear protein and potent tight-binding inhibitor of several cyclin/Cdk complexes, playing a role in maintenance of the nonproliferative state of cells. The mirror phenotype of BWS and IMAGe can be, at least in part, explained by the effect of mutations on protein functions. All the IMAGe-associated mutations are clustered in the proliferating cell nuclear antigen-binding domain of CDKN1C and cause a dramatic increase in the stability of the protein, which probably results in a functional gain of growth inhibition properties. In contrast, BWS mutations are not clustered within a single domain, are loss-of-function, and promote cell proliferation. CDKN1C is an example of allelic heterogeneity associated with opposite syndromes
Genetics of Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome
No full textMayer-Rokitansky-Küster-Hauser (MRKH) syndrome, also referred to as Müllerian agenesis, is the second most common cause of primary amenorrhea. It is characterized by congenital absence of the uterus, cervix, and the upper part of the vagina in otherwise phenotypically normal 46,XX females. MRKH syndrome has an incidence of about 1 in 4,500-5,000 newborn females and it is generally divided into two subtypes: MRKH type 1, in which only the upper vagina, cervix and the uterus are affected, and MRKH type 2, which is associated with additional malformations generally affecting the renal and skeletal systems, and also includes MURCS (MÜllerian Renal Cervical Somite) characterized by cervico-thoracic defects. MRKH syndrome is mainly sporadic; however, familial cases have been described indicating that, at least in a subset of patients, MRKH may be an inherited disorder. The syndrome appears to demonstrate an autosomal dominant inheritance pattern, with incomplete penetrance and variable expressivity. The etiology of MRKH syndrome is still largely unknown, probably because of its intrinsic heterogeneity. Several candidate causative genes have been investigated, but to date only WNT4 has been associated with MRKH with hyperandrogenism. This review summarizes and discusses the clinical features and details progress to date in understanding the genetics of MRKH syndrome
A patient defines the interstitial 1q deletion syndrome characterized by antithrombin III deficiency
No full textA patient with microbrachycephaly, high forehead, long philtrum, thin upper lip, downturned corners of the mouth, low set ears with overlapping helix, fifth-finger clinodactyly, small hands and feet, bilateral transverse palmar crease, low total finger ridge count, hypotonia, severe growth and psychomotor delay, mild hypoplasia of corpus callosum, and Arnold-Chiari type 1 malformation is reported. The karyotype showed 46, XY, del(1)(q23q31.2). Coagulation factor V (F5, 1q23) and coagulation factor XIII (F13B, 1q31-q32.1) levels were normal. As expected, antithrombin III (AT3, 1q23-q25.1) serum level and activity were half of normal. We performed a review of the literature on proximal and intermediate deletion 1q syndrome, and we hypothesize the existence of only one 1q interstitial deletion syndrome, clinically characterized by ATIII deficiency
Challenging the orthodoxy of value-cocreation theory: a contingent view of co-production in design-intensive business services
No full textThis interview-based study of three design-oriented KIBS firms proposes a U-shaped project-stage model of co-production intensity in firms offering knowledge-intensive business services (KIBS) requiring a high level of creativity. The study suggests that, under certain circumstances, both KIBS providers and clients might desire to regulate the level of co-production, and that at certain project stages a reduced level might actually improve the quality of the final output
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