Novel Machine Learning Approach for Defect Detection in DFT Processes

Recent advances in semiconductor technology have highlighted significant challenges in effectively testing modern integrated circuits (ICs). As device densities increase and defect mechanisms become more diverse, conventional Design for Testability (DFT) methodologies – while indispensable – must contend with exponential growth in test complexity. This paper reviews the essential DFT practices, including scan-based structures, boundary scan, and built-in self-test (BIST), and examines how these practices address a variety of logical fault models. It further explores machine learning (ML) techniques as valuable tools for enhancing defect detection and diagnosis. By leveraging classification algorithms such as support vector machines and neural networks, ML-driven approaches can reduce test pattern generation time, improve bridging-fault coverage, and streamline board- or wafer-level screening. Collectively, this paper underscores how strategic synergy between DFT and ML can raise fault coverage, improve diagnostic precision, and contain testing costs in the face of ongoing technology scaling

Deciphering the molecular mechanisms underlying complex traits using bioinformatics and computational biology approaches

With the advent of high-throughput sequencing technologies, multi omics studies (genomics, transcriptomics, proteomics, and metabolomics) are becoming increasingly popular to decipher the molecular patterns in association with a disease/biological process. Access to such data has revolutionized the field of agriculture and it provides novel perspectives for several systems biology studies. Furthermore, the usage of multi-omics data has proven to be powerful and accurate to study the biological processes in association with the growth, development, adaptation and disease progression in an organism. Moreover, systems biology approaches enabled the integration of multi omics data to create a holistic understanding of the molecular mechanisms underpinning complex traits. In this thesis, I present the application projects which investigate the molecular mechanisms underlying the complex traits involved in (i) African Animal Trypanosomiasis disease progression in cattle breeds and (ii) the seed oil content of the oil crop Brassica napus. Regarding my first project, African Animal Trypanosomiasis (AAT) is a disease caused by pathogenic trypanosomes which affects millions of livestock every year causing huge economic losses in agricultural production especially in sub-Saharan Africa. The disease is spread by the tsetse fly which carries the parasite in its saliva. During the disease progression, the cattle are prominently subjected to anaemia, weight loss, intermittent fever, chills, neuronal degeneration, and congestive heart failure. According to their different genetic programs governing the level of tolerance to AAT, cattle breeds are classified as either tolerant or susceptible. I focussed on the cattle breeds N’Dama and Boran which are known to be tolerant and susceptible to trypanosomiasis, respectively. Despite the rich literature on both breeds, the gene regulatory mechanisms of the underlying biological processes for their resistance and susceptibility have not been extensively studied. To address the limited knowledge, I analyzed a continuous transcription profiling time-series microarray dataset obtained from three tissues (liver-, spleen-, and lymph node tissues) of the two cattle breeds Boran and N’Dama, after being infected with Trypanosoma congolense. I attempted to capture the transcriptional events while considering the multistage progression process of AAT disease through the identification of monotonically expressed genes (MEGs). As a result, I identified several tissue-specific transcription factor (TF) cooperations for the tissues of both cattle breeds and explained the role of preferential partner choices of TFs in association with the trypanosusceptibility and trypanotolerance mechanisms. Furthermore, I focussed on the upstream regulatory processes underlying the multi-stage progression process of the AAT disease by identifying the unique, cattle breed-specific master regulators and over-represented signalling pathways for these two cattle breeds, respectively. Moreover, I deciphered the influence of downstream regulatory events involving the effector molecules and their complex interplay with the regulatory SNPs and gene expression. In order to test the applicability of the bioinformatics pipeline from the first project on other species, I investigated the transcriptional regulation involved in governing the seed oil content in Brassica napus L. Knowledge regarding transcriptional regulation is crucial to gain insights into the developmental switches between the cultivars of Brassica napus, namely Zhongshuang11 (ZS11), a double-low accession with high-oil- content, and Zhongyou821 (ZY821), a double-high accession with low-oil-content. In my second project, I analyzed a time series RNA-seq data set of seed tissue from both cultivars by mainly focusing on the MEGs. The consideration of the MEGs enables the capturing of a multi-stage progression process that is orchestrated by the cooperative TFs and, thus, facilitates the understanding of the molecular mechanisms determining seed oil content. In this study, I reported that TF families, such as NAC, MYB, DOF, GATA, and HD-ZIP, are highly involved in the seed developmental process. Particularly, their preferential partner choices as well as changes in their gene expression profiles seem to be strongly associated with the differentiation of the oil content between the two cultivars. In summary, my application project in animal sciences provides insights into genetic programs governing the susceptibility and tolerance mechanisms in cattle breeds Boran and N’Dama and therefore provides novel targets for therapeutic implications and future breeding programs. My second application project resulted in several potential targets for breeding purposes with respect to seed oil content in two cultivars of Brassica napus.2022-12-1

On the implausibility of slow-switching arguments in establishing incompatibility thesis

Philosophers who argue that content externalism is incompatible with authoritative self-knowledge usually employ one of the two arguments namely the slow-switching argument and the reductio ad absurdum. Of these I focus on only the former which in itself has two variants namely the content-switch (main argument) and the memory argument (a variant). I argue against both the variants thereby denying that slow-switching arguments succeed in establishing the incompatibility thesis. It is long held that if a slow-switched agent (Oscar) were to stay long enough on twin earth, his thought contents change unbeknownst to him. And it was reasoned that, since Oscar is unaware of the changes in his mental contents and cannot spot when the changes occurred, he does not have access to his own thought contents at all times, which thereby leads to the conclusion that authoritative self-knowledge is incompatible with externalism. In this thesis, I argue that, in cases like these, mental contents do not change unknown to Oscar. I appeal to theories of concept acquisition to achieve this end. This forms my attack on the main argument. And, as against the memory argument, I use two strategies the first one of which is an extension of the previous argument applied to this case; and the second strategy is to argue that memorial recollection depends on the past, and not the present, environment and, if Oscar does not forget any relevant past stimuli, his memorial contents upon recollection will not change. Having thus argued against both the variants of the slow-switching arguments, I conclude that slow-switching arguments do not succeed in establishing the incompatibility thesis.https://www.ester.ee/record=b5242461*es

A Note On ℓ\ell-Rauzy Graphs for the Infinite Fibonacci Word

The $\ell$-Rauzy graph of order $k$ for any infinite word is a directed graph in which an arc $(v_1,v_2)$ is formed if the concatenation of the word $v_1$ and the suffix of $v_2$ of length $k-\ell$ is a subword of the infinite word. In this paper, we consider one of the important aperiodic recurrent words, the infinite Fibonacci word for discussion. We prove a few basic properties of the $\ell$-Rauzy graph of the infinite Fibonacci word. We also prove that the $\ell$-Rauzy graphs for the infinite Fibonacci word are strongly connected.Comment: 10 pages, 4 figure

A new configuration of multilevel inverter to generate higher voltage level with lower components

Nowadays, the demand for cleaner and higher quality electricity supply is increasing among various industries and individual consumers. When compared to conventional two-level inverters, multi-level inverters are becoming more and more common, as these inverters deliver high-quality power with fewer harmonics. Here a new multilevel inverter circuit designed with variable direct current (DC) voltage sources is proposed, this circuit requires limited circuit components, and is compared with the other topologies with the same voltage in the output. The proposed topology requires nine switches in order to generate a single-phase 13-level output voltage without connecting to a polarity-generating circuit. The output voltage level and performance parameters associated with the total harmonic distortion (THD) of the voltage level in the output generated by the proposed multilevel inverter or MLI are evaluated in a MATLAB environment. The final simulation results confirm the behavioral accuracy in the proposed topology while creating all the levels. Also, real-time work is done to verify the operation of the inverter and the results are showcased

A Study on Social Adjustment Among Elderly Inmates Convicts Central Prisons of Tamil Nadu

Tamil Nadu prisons house a growing number of aging inmates facing hardships in correctional facilities. Some cope with old bones suffering in cold winter sessions without mattresses, lack wheelchairs or walkers, and cannot afford portable oxygen or hearing aids. So many Elderly inmates very difficult to even dressing, going to the bathroom or bathing without assistance. The research reveals the plight of inmates who are incontinent, forgetful, suffering from chronic illnesses, severe ailments, and many who are dying while growing old behind bars. Objective: To study the socio-economic conditions of Elderly Inmates Convicts. To assess Social Adjustment among Elderly Inmates Convicts. Material and Method: This study utilized both qualitative and quantitative methods to examine Social Adjustment among Elderly inmate’s convicts in central prisons of Tamil Nadu. A descriptive research design was employed, and the sample was selected through purposive sampling. Five Central Prisons were chosen from a total sample size of 213, located in Tamil Nadu State, India: Cudalore, Madurai, Tirunelveli, Tiruchirappalli and Vellore. Results: The major findings of the research study include the following 47 percent of elderly inmates are in the age group 60-65 years, and 24 percent are between 66-70 years. 77.9 percent of elderly individuals are from rural areas. 46.5 percent have primary-level educational qualifications and have committed crimes for emotional reasons. 89.7 percent of the elderly inmates who committed crimes were married. 59 percent of respondents have a family income ranging from Rs.1000 to Rs. 5000, indicating vulnerable socio-economic conditions. 43 percent of elderly inmates are involved in farming, while 30 percent engage in labor work.61 percent of respondents belong to nuclear families, and the complex connections between various individual and environmental factors contribute to mental illness in elder convicts. 86 percent of respondents have a Hindu religious background, with current research lacking and inadequate services for elderly prisoners suffering from mental illness. 66 percent of respondents committed murder, 18 percent sexual offenses, 8 percent attempted murder, 6 percent corruption cases & 2 percent kidnapping, and harboring offenders. 51 percent of respondents face a lifetime punishment. The research used a social adjustment scale for the aged to analyze aspects such as Family, Spouse, Interpersonal Relations, Health, and Financ

Individual case safety reports by nursing staff: a retrospective pharmacovigilance analysis

Background: The burden of adverse drug reactions is high and accounts for considerable morbidity which can be prevented if healthcare professionals have proper knowledge. Early and spontaneous reporting of ADRs is the mainstay of pharmacovigilance program. Since staff nurses are closely involved in direct patient care, they can easily identify ADRs in the early stage. This study was done to assess the extent of participation of nurses in pharmacovigilance program in our institution.Methods: Retrospective observational study was conducted by analyzing the 210 Individual Case Safety Reports (ICSR) of 2years duration. Causality assessment in the ICSR was analyzed. Severity of the reactions was categorized into mild, moderate and severe according to Modified Hartwig and Siegel scale. Descriptive statistics were used.Results: There were 177 cases reported by faculties and 33 were by the staff nurses.19 nurses reported 33 adverse effects (1:1.7) whereas 41 faculties 177 events (1:4). On analyzing the severity of reactions, 188 cases were categorized as moderate (89.5%), 20 mild (9.5%) and 2 severe (1%). In moderate category of 188 reports, 82 % reporting was by faculties and 18% by staff nurses. All the 33 reports by nurses were of moderate category (100%). In the mild and severe category, 100% reporting was by faculties. Causality analysis showed that 194 were classified as probable (92%), 14 as Possible (7%) and 2as certain (1%). In probable category 85% of reporting was by faculties and 15% by nurses, in possible group 71 % by faculties and 29% by nurses and 100% by faculties in severe category.Conclusions: Training and dedicated participation of nurses can improve reporting of ICSR