NUST Institutions Library Catalogue Search for 'kw,wrdl: su-br:an:"1223"'

Handbook of ambient intelligence and smart environments \

By Nakashima, Hideyuki.. New York : Springer, 2010 9780387938073 (hbk.)

Place Hold on Handbook of ambient intelligence and smart environments \

ATM VOl-III Internetworking with ATM

By Black, Uyless D.. Englewood Cliffs, N.J. : Prentice Hall PTR, 1995 . v. <1, 3> : 25 cm.. 013297178X (v. 1) | 0137841825 (v. 3)

Place Hold on ATM VOl-III

How to teach reading successfully /

By McNeil, John D.. Boston : Little, Brown, 1980 . xi, 404 p. : 24 cm.. 0316563064

Place Hold on How to teach reading successfully /

Effect of Hygrothermal Aging on Strength Performance of Cork Powder Reinforced Adhesive /

By Sohail, Zulekha . . 100p. , Adhesives play a crucial role across various industries and applications due to their ability to bond materials together. They are used in numerous ways, ranging from everyday household applications to industrial and specialized fields. Strength is the most critical factor to analyze before using the adhesive. Various techniques have already been developed and many are being developed to predict and improve the strength of adhesive. The addition of cork powder to the structural adhesives could improve the strength of adhesive joints through mechanical interlocking between the cork cells and the molecules of adhesive. However, even with the nanofiller reinforcement, the strength of adhesive joints is significantly affected by environmental parameters like temperature and humidity. The present study investigated the effect of hydrothermal aging on the strength characteristics of cork powder-reinforced adhesive samples. Reinforced adhesive samples were investigated under two different humidity levels of 80% and 100% RH. The cork powder will be added in concentration of 0.25wt.%, 0.5wt.%, 0.75wt.% and 1wt.% to study the reinforcing effects. The result shows that the saturated mass increased with increased in relative humidity that is approximately 0.4% and 0.9% for 80% and 100% RH respectively. The findings show that the ultimate tensile strength is reduced by the addition of cork powder as well as enhancing humidity. Furthermore, the addition of cork powder makes the sample more brittle, so failure strain and tensile toughness undergo decrement. The above finding indicated that hot-wet environment has a negative influence on strength performance of cork powder reinforced adhesive. In future the same study can be performed to know the strength of SLJ and DLJ to know its effect on joints. 30cm.

Place Hold on Effect of Hygrothermal Aging on Strength Performance of Cork Powder Reinforced Adhesive /

Estimation of cognitive state improvement using EEG brain imaging after tDCS stimulation therapy /

By AYUB ,MUDASSAR. . 88p. ; 30cm..

Place Hold on Estimation of cognitive state improvement using EEG brain imaging after tDCS stimulation therapy /

Functional Characterization Of Risk Factor Involved In Mptp-Induced Parkinsonism In Mice /

By Jatala, Faria Hasan . . 72p. , The second-most prevalent neurological disease in the world, Parkinson's disease (PD) affects roughly 4 million people. The death and loss of dopaminergic neurons in the substantia nigra compacta (SNpc) is the primary pathogenic characteristic of PD. Motor abnormalities include limb stiffness, tremor, and bradykinesia are the major features of PD. Although levodopa (L-DOPA) is the gold standard medication, but it has clear negative effects when taken over an extended period. Therefore, it is vital that novel medicines and ideal therapeutic agents be discovered. Parkinson's disease remains an unsolved clinical problem, as currently authorized PD therapies offer relatively modest therapeutic benefits. New therapeutic approaches that not only alleviate symptoms in the short term but also stop the disease from getting worse are desperately needed. For this purpose, mice model is utilized for PD induction by MPTP neurotoxin for functional characterization of proteomic factor GFAP as a risk factor in an effort to enhance the efficacy of the treatment of PD. In future, by targeting pathway of GFAP level in substantia nigra with some targeted drug will eventually lead to innovative therapeutic approach for PD patients. 30cm.

Place Hold on Functional Characterization Of Risk Factor Involved In Mptp-Induced Parkinsonism In Mice /

COVID-19 (6LU7) predictive binding association with Aβ oligomers and possible link to Alzheimer's disease /

By Khan, Areej Sohail . . 74p. , The high rise pandemic of Coronavirus Disease 2019 (COVID-19) makes the world face medical challenges associated with multifaceted nature of its pathology. SARSCoV-2 affects several organs and systems as it enters the host’s body one of which is the brain. Over 80 million humans around the globe, including those with neurodegenerative disease (NDD), have been diagnosed with coronavirus disease 2019 (COVID-19) to date. COVID-19 affects the brain in many ways including direct infection of neural cells with SARS-CoV-2, severe systemic inflammation that floods the brain with pro-inflammatory agents leading to damaging cells and leading to symptoms presenting cognitive impairment. COVID-19 positive patients showcase neurological symptoms leading to the belief that coronavirus disease plays a role in neurodegenerative diseases. The most common NDD, Alzheimer’s disease (AD) is characterized by its multifactorial nature leading to research on risk factors that emphasizes on the inflammation of toxicity and mutual death of cells due to amyloid beta and its conformers, namely monomeric and oligomeric forms. Amyloid beta oligomers initiate toxicity and neural death of cells in AD. The main aim of this study is to decipher the interactive association between toxic forms of amyloid beta oligomer against COVID-19 main protease. We used PDB and Pubchem for library retrieval that was loaded in to discovery studio to extract the active binding site of main protease of SARS-CoV-2 and prepare ligands for docking. Furthermore, we utilized PyRx for docking to investigating binding energies of conformations attained, the best affinity ligands were formed into a complex by the use of Pymol that were than visualized using Discovery studio where 2D interactions were also observed that later were further analyzed using Ligplot+ to get an insight on bond length and strength along with bond types. Aβ oligomer 31-35 binds actively to the active site of M-pro of SARS-CoV-2 at a high affinity rate of -6.3kcal/mol. 6LU7 complex with amyloid 31-35 (Complex 1) when docked XII with the receptor of apoptotic pathway showed enhanced predictive association. Bioinformatics tools in this research substantiated the important interactive partners amongst amyloid oligomers to COVID-19 highlighting that SARS-Cov-2 may play a role in apoptotic demise of cells ultimately leading to neurodegeneration. 30cm.

Place Hold on COVID-19 (6LU7) predictive binding association with Aβ oligomers and possible link to Alzheimer's disease /

Comparison of Different Machine Learning Models for Quality Control in Biscuit Manufacturing Industry of Pakistan /

By Awais, Muhammad . . 113p. , Ensuring consistent product quality is a critical challenge in the biscuit manufacturing industry, particularly in developing economies like Pakistan, where manual inspection remains the norm. This approach, however, is prone to human error, fatigue, and inconsistency, leading to variable quality control outcomes. This research proposes an intelligent, machine learning–based automated quality inspection system tailored for real-world biscuit production lines. A comprehensive dataset of 40,000 high-resolution images was curated, representing four popular biscuit varieties Rio, Sooper, Candy, and Marie captured under actual factory lighting conditions. The dataset includes both defective and non-defective samples, covering a wide range of defect types such as breakage, charring, deformation, and missing pieces. To ensure high-quality annotations with scalable efficiency, a semi-automated iterative annotation framework was developed, combining initial manual labeling with model-assisted annotation and human-in-the-loop refinement across multiple cycles. Multiple state-ofthe-art machine learning models were implemented, fine-tuned, and rigorously evaluated, including YOLOv8, YOLOv11, YOLOv12, Faster R-CNN (via Detectron2), and Vision Transformer (ViT-B/16). Models were assessed using key performance metrics such as mAP@0.5:0.95, precision, recall, F1-score, inference speed (FPS), and computational efficiency. The results demonstrate that modern deep learning models, particularly YOLOv12 and Vision Transformers, achieve high detection accuracy (mAP > 90%) while maintaining feasibility for real-time deployment when optimized. This study provides a comparative analysis of accuracy-speed trade-offs, offering actionable insights for manufacturers seeking cost-effective, scalable solutions. The research concludes with practical recommendations for integrating AI-driven inspection systems into existing production infrastructure in resource-constrained environments, balancing performance, hardware requirements, and long-term maintainability. 30cm.

Place Hold on Comparison of Different Machine Learning Models for Quality Control in Biscuit Manufacturing Industry of Pakistan /