1,723,496 research outputs found
Photo of Cecilia and Kaleem Noah sitting in their home, Weston Cottage.
No full textA photograph of Kaleem and Cecilia (nee Koritem) Noah in their home at Weston Cottage. A photograph of a younger Kaleem is visible behind them
고온 가스 냉각로 내의 원자로 흑연의 산화와 연소 반응에 대한 수학적 모델링
No full text학위논문(석사) - 한국과학기술원 : 원자력및양자공학과, 2005.8, [ v, 39 p. ]We investigated the oxidation of nuclear grade graphite IG-110 in HTGRs, which is influenced by boundary layer conditions and in pore diffusion of oxygen. After exposure to oxygen the concentration profile and the total mass transfer rate of oxygen in a IG-110 cylinder was calculated by modeling with Shell mass balance and solving the resulting differential equation. The concentration profile of oxygen and effectiveness factor were estimated using experimental data. It turns out that the oxygen concentration profile is nearly uniform when the graphite temperature is lower than 700℃. In addition, variation of concentration of oxygen in a IG-110 cylinder with respect to temperature was also calculated. It shows that oxygen concentration reduces to zero at a distance from the exterior surface less than radius of the cylinder (r) above 900℃. Finally, a model for predicting burn-off behaviour is obtained through the investigation of the variation of interfacial area density with burn-off.한국과학기술원 : 원자력및양자공학과
Fluid mechanics and machinery / Mohd. Kaleem Khan (Assistant Professor, Department of Mechanical Engineering, Indian Institute of Technology, Patna).
No full textIncludes index.engineering bookfair2016xx, 627 pages
From detailed acoustic analysis to AI: designing and developing advanced speech analysis tools
No full textThe modernization of the xkl software, originally developed by Dennis Klatt at MIT in the 1980s, was a major goal of this research work. The introduction of a new Graphical User Interface (GUI), using GTK libraries, simplified the installation process but most importantly made the software accessible and user-friendly on various platforms, including Windows, Linux, and MacOS. The xkl refurbishment also addressed the inclusion, in the spectrum processing tools of the so-called reassigned spectrogram, allowing thus for improved detailed examination of speech spectra. In the current xkl version, formant values are now automatically saved in a text file, which facilitates largescale analysis, especially for vowels studies. The development of a modern xkl speech analysis tool was part of the LaMIT project [1], that has the goal of applying Stevens lexical access model [2] to the Italian language. One major innovation introduced by Stevens is the concept of landmark, that is, the presence of privileged regions in the time domain at which a primary phase of the perceptual process would take place, the landmark positions. In this work, an automatic vowel landmark detector was developed. This landmark recognition system was developed and implemented based on a Convolutional Neural Network combined with a Recurrent Neural Network, i.e. a CNNRNN hybrid model. The CNN-RNN recognizer used a set of parameters that combined energy measurements and Mel-spectrum descriptors, and was run on the above sentences. The recognizer was tested on sentences of the LaMIT database [3], a corpus formed by 800 spoken utterances (4 native italian speakers) that were manually analyzed by examining the corresponding speech waveforms but most importantly using the xkl tool that provided invaluable information on spectral general properties and time-varying spectral properties. It is thanks to this analysis that the corpus was manually labeled and contains now information about landmark presence, landmark type, and landmark position in time. The output of the recognizer produced an estimation of detected vowel landmarks. This output was compared against the manually estimated vowel landmark presence. The overall recognition rate was 74.98%. For individual speakers the recognition rate ranged from about 72% to about 77%. Artificial intelligence methods were also applied to automatic foreign accent identification [4]. A Multi-Kernel Extreme Learning Machine (MK-ELM) model, along with a weighted scheme, was proposed for application to the recognition of 5 different accents (Arabic, Chinese, Korean, Spanish, French) in American English. The recognition was based on Mel-frequency cepstral coefficients (MFCC) and prosodic features (Pitch, Energy). The proposed model achieved an accuracy rate of 84.72% using a paired weighting scheme. In contrast, the accuracy rate dropoped to 66.5% when employing the traditional non-weighted multi-classification scheme. A comparison against other other state-of-the-art classification methods showed significant advantages of the proposed model
UNVEILING THE HIDDEN REPERTOIRE OF GLIOBLASTOMA TUMOR ANTIGENS BY GENETIC MODOFICATION OF TUMOR CELLS WITH THE MHC CLASS II TRANSACTIVATOR CIITA
Get PDFIl glioblastoma (GBM) è uno dei tumori cerebrali più aggressivi e mortali, noto per la sua capacità di eludere il sistema immunitario del corpo e resistere ai trattamenti tradizionali. Per affrontare questa sfida, abbiamo esplorato un nuovo approccio di immunoterapia utilizzando il MHC classe II transattivatore (CIITA) per aiutare il sistema immunitario a riconoscere e mirare cellule GBM in modo più efficace.
In questo studio, abbiamo modificato tre diverse linee cellulari murine GBM (GL261, CT-2A e SB28) per esprimere CIITA. Questa modificazione ha significativamente indotto e/o aumentato i livelli di molecole MHC-II e MHC-I sulle loro superfici, che sono cruciali per la presentazione al sistema immunitario delle proteine (antigeni) associate ai tumori. Con questi antigeni diventando più visibili, le cellule T del sistema immunitario, comprese sia le cellule T aiutanti (CD4+) che killer (CD8+), potrebbero meglio identificare e attaccare il tumore. in vitro proliferazione ha ulteriormente confermato che l'espressione CIITA non ha influenzato il tasso di crescita delle cellule tumorali, indicando che eventuali cambiamenti nel comportamento del tumore sarebbe dovuto solo alla risposta immunitaria piuttosto che alterazioni nelle cellule stesse.
Abbiamo poi valutato questa strategia nei topi utilizzando diverse combinazioni di vaccini GL261-CIITA e sfide. Questo studio si concentra sui topi che sono stati inizialmente vaccinati con le cellule GL261-CIITA modificate e successivamente sfidato con le cellule tumorali aggressive SB28. Sorprendentemente, il 75% dei topi vaccinati ha completamente respinto le cellule tumorali e il restante 25% ha mostrato una crescita del tumore ridotta rispetto ai topi non vaccinati. L'analisi di immunoistochimica (IHC) ha rivelato una forte risposta immunitaria, con chiare indicazioni di infiltrati di cellule T che prendono attivamente di mira il tumore.
Per comprendere meglio la protezione in questi topi, specialmente nel contesto di sfide eterogenee, abbiamo impiegato la spettrometria di massa per identificare i peptidi specifici che sono presentati dalle cellule tumorali modificate. Curiosamente, molti di questi peptidi erano condivisi tra le tre linee cellulari e erano anche simili a quelli trovati nelle cellule umane GBM, suggerendo il potenziale traslazionale del nostro approccio alle impostazioni cliniche. Questa maggiore presentazione di antigene da parte delle cellule modificate con CIITA potrebbe servire come base per un nuovo vaccino ad ampio spettro contro il GBM.
I nostri risultati suggeriscono anche che aumentare la capacità del sistema immunitario di riconoscere e rispondere alle cellule GBM utilizzando CIITA può innescare una potente risposta anti-tumorale. Questa strategia non solo aiuta a combattere il tumore iniziale, ma suggerisce anche la possibilità di una protezione incrociata contro diversi tipi di GBM.Glioblastoma (GBM) is one of the most aggressive and deadly brain tumors, known for its ability to evade the body's immune system and resist traditional treatments. To tackle this challenge, we have explored a new immunotherapy approach using the MHC class II transactivator (CIITA) to help the immune system to recognize and target GBM cells more effectively.
In this study, we have modified three different murine GBM cell lines (GL261, CT-2A, and SB28) to express CIITA. This modification has significantly induced and/or increased the levels of MHC-II and MHC-I molecules on their surfaces, which are crucial for presenting tumor-associated proteins (antigens) to the immune system. With these antigens becoming more visible, the immune system's T cells, including both helper (CD4+) and killer (CD8+) T cells, could better identify and attack the tumor. in vitro proliferation assays has further confirmed that CIITA expression did not affect the growth rate of the tumor cells, indicating that any changes in tumor behavior would solely be due to the immune response rather than alterations in the cells themselves.
We then have evaluated this strategy in mice using different combinations of GL261-CIITA vaccinations and challenges. This study focuses on mice that were initially vaccinated with the modified GL261-CIITA cells and later challenged with aggressive SB28 tumor cells. Remarkably, 75% of the vaccinated mice has completely rejected the tumor cells, and the remaining 25% has showed reduced tumor growth compared to non-vaccinated mice. Immunohistochemistry (IHC) analysis has revealed a strong immune response, with clear indications of T-cell infiltrates actively targeting the tumor.
To further understand the protection in these mice, especially in the context of heterogeneous challenges, we have employed mass spectrometry to identify the specific peptides that are presented by the modified tumor cells. Interestingly, many of these peptides were shared among the three cell lines and were also similar to those found in human GBM cells, suggesting the translational potential of our approach to clinical settings. This increased antigen presentation by CIITA-modified cells could serve as the foundation for a new, broad-spectrum GBM vaccine.
Our findings also suggests that boosting the immune system's ability to recognize and respond to GBM cells using CIITA can trigger a powerful anti-tumor response. This strategy not only helps in fighting off the initial tumor but also suggests potential for cross-protection against different types of GBM
Religion and finance: Comparing the approaches of Judaism, Christianity and Islam
No full textKaleem, A ORCiD: 0000-0002-0939-9922This book examines each of these three major world faiths, considering their teachings, social precepts and economic frameworks, which are set out as a guide for the financial dealings and economic behaviour of their adherents
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