Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulation of n-FinFET Performance Reliance on Varying Combinations of Gate Material and Oxide

In this paper an n-type double gate FinFET at a gate length of 22nm is reported. Here the device performance of FinFET under different gate materials and also under different buried oxides is construed. Firstly, the drain current under different gate materials, with different work functions and SiO2 being the buried oxide has been obtained. A transfer characteristic curve has then been obtained comparing the drain current for different gate materials at a given supply voltage of 0.5 V. Secondly, the transfer characteristic curve, comparing the drain currents obtained under different buried oxides at 0.5 V supply voltage with Aluminium being the gate has been obtained. And lastly obtained is the device performance for different combinations of gate materials and buried oxides and the results were compared. It can be inferred that, a metal gate and a high k dielectric is what gives a good performance at nanometre ranges. All the simulations have been done in Visual TCAD.
Who should be prioritized? : the impact of meritocracy norm on medical decisions toward a low status group

This dissertation investigates whether (a) social status predicts prioritization in medical decisions and (b) whether the salience of meritocracy explains the effect of patient’ social status on those decisions. When deciding about prioritizing patients for a treatment or a medical procedure, providers rely on medical evidence and on the symptoms expressed by patients (Dovidio & Fiske, 2012). However, research shows a systematic disproportionate negative impact of medical decisions on members of low-status groups, such as racialized immigrant groups (Hicken et al., 2018; Smedley, et al., 2003). In previous research, implicit prejudice, stereotyping, and conservative ideologies were found to explain, at least under certain circumstances, statusbased differentials in medical outcomes (Green et al., 2007). In the present thesis, we offer a novel and complementary perspective: the influence of social norms. In particular, we examine whether the Meritocracy norm explains differences in the prioritization, as a function of patient’ social status. We do so by investigating the impact of Meritocracy on socially critical decisions in the medical context and involving a low status group, the African immigrants. We propose medical decisions to be less favorable toward the low status group, particularly when the meritocracy norm is salient; thus, meritocracy norm is conceptualized as a moderator of the relationship between social status and medical decisions. We also propose that the adverse effect of meritocracy should operate when it is possible to infer a person's personal responsibility for the state of health and when the legitimizing meaning of meritocracy is salient. Particularly, we propose that in a situation involving medical decisions, such as transplants or expensive medical treatments, meritocracy operates through its legitimizing meaning, which may reduce the preference for members of socially disadvantaged groups. We present empirical evidence that provides general support for the hypotheses in seven studies and a systematic review analyzing, in medical settings, how the intergroup biases of the Portuguese towards the low status group portrayed are reinforced and legitimized in the presence of meritocracy, a social norm that regulates social relations.
Nutritional effects on foetal growth

The emphasis in nutritional studies on foetal growth has now moved from the last trimester of pregnancy, when most of the increase in foetal size takes place, to earlier stages of pregnancy that coincide with foetal organogenesis and tissue hyperplasia. At these stages absolute nutrient requirements for foetal growth are small but foetal metabolic activity and specific growth rate are high. It is thus a time when nutrient supply interacts with maternal factors such as size, body condition and degree of maturity to influence placental growth and set the subsequent pattern of nutrient partitioning between the gravid uterus and maternal body. Throughout pregnancy the maternal diet controls foetal growth both directly, by supplying essential nutrients and indirectly, by altering the expression of the maternal and foetal endocrine mechanisms that regulate the uptake and utilization of these nutrients by the conceptus. Nutritional effects on the endocrine environment of the embryo during the early stages of cell division can alter the subsequent foetal growth trajectory and size at birth; so too can current in vitro systems for oocyte maturation and embryo culture up to the blastocyst stage. There is increasing evidence that subtle alterations in nutrient supply during critical periods of embryonic and foetal life can impart a legacy of growth and developmental changes that affect neonatal survival and adult performance. Identifying the specific nutrients that programme these effects and understanding their mode of action should provide new management strategies for ensuring that nutritional regimens from oocyte to newborn are such that they maximize neonatal viability and enable animals to express their true genetic potential for production.
Analytical Assessment of Dual-Stream Merging for Noise-Robust ASR

In previous studies (on Aurora2), it was found that merging a posteriori probability streams from different classifiers (GMM, MLP, Sparse Coding) can improve the noise robustness of ASR. Maximizing word accuracy required the stream weights to be systematically dependent on the specific input streams and SNR. The tuning of the weights, however, was largely a matter of trial and error and typically involved a laborious grid search. In this paper, we propose two fundamental, analytical methods to better understand these empirical findings. To that end, we maximize the trustworthiness of merged streams as function of the stream weights. Trustworthiness is defined as the probability that the winning state in a probability vector correctly predicts a golden reference state obtained by a forced alignment. Even though our approach is not directly equivalent to optimizing word accuracy, both methods appear highly useful to obtain insight in stream properties that determine the success of a given merge (or the lack thereof). Furthermore, both methods clearly support the trends that exist in the grid-search based empirical observations.
Efficacy of Two Pheromone Types on Red Palm Weevil, Rhynchophorus ferrugineus Under Saudi Arabian Conditions

Two types (Trece incorporated, USA) of synthetic aggregation pheromone lures (8683 and 8685) were used to trap the adults of red palm weevil (RPW), Rhynchophorus ferrugineus (Oliver), in infested date palm farm at Al-Jush in Al-Qatif district, Eastern Province, Saudi Arabia, by using the reusable Saudi bucket trap. Adult weevils (females and males) were attracted to both types of pheromones although females were found more in number than males. Type 8683 pheromone was most attractive to RAW than type 8685 and the highest number of weevil captures were recorded during the months of February, March and April.
Using new methods to understand how fault properties influence earthquake properties

In this thesis, I investigate the interaction of aseismic slip with earthquake stress drops and the interaction of fault properties with properties of repeating earthquakes. I use and develop a new inter-station phase coherence-based approach to estimate the rupture extents and stress drops of earthquakes. This new method is sensitive to different properties than spectral corner frequency approaches, and may be useful for examining properties such as rupture velocity. I use the phase coherence method to examine how stress drops vary with aseismic slip. The seismic coupling, and thus aseismic slip, varies along the Blanco fault. I find that the stress drops of earthquakes in areas with more aseismic slip are lower than earthquakes in areas with less aseismic slip, which may be caused by a shortened seismic cycle on the hotter, more aseismic section of the fault. I also examine stress drops of aftershocks of the 2010 M_W 7.2 El Mayor-Cucapah earthquake to test whether changes in post-seismic slip rate cause changes in stress drops of aftershocks. The result of this comparison is unclear, but I find that the phase coherence method can be applied to the P wave and S wave which is useful for noisy datasets. Finally, I examine repeating earthquakes in Parkfield, California to test whether the observed recurrence interval-moment scaling M_0^1/6 is due to spatially variable slip rates on a fault. In this hypothesis, repeating earthquakes occur on smaller faults with lower slip rates and recurrence interval-moment scaling reflects the scaling of slip rate with fault length. I find that the recurrence interval-moment scaling of repeating earthquakes varies with the distance between sequences, which suggests that repeating earthquakes occur on smaller, lower slip rate faults. This result suggests that repeating earthquake properties may reflect fault properties rather than the amount of aseismic slip.
Security Enhancements over AODV Using Multi-hop Acknowledgment

In most applications of Mobile Ad-hoc Networking and Wireless Sensor networks (WSNs), security and power consumption is a recurring problem which is very difficult to solve due to unpredictable behaviour, environmental changes and mobility of nodes. TERP is a Trust based Energy Routing Protocol that considers the energy conservation and security aspects of WSNs. It is an improved version of AODV and ensures low power consumption while adding a trust based system to the reactive nature of AODV. It also provides the solutions for the most basic attacks like node selfishness, spoofing, misbehaviour and packet sniffing. But black-hole attack, gray-hole attack, Sybil and wormhole attacks are yet to be addressed in the TERP. This paper provides a solution to detect and prevent the node misbehaviour and gray-hole attack. TERP identifies the node misbehaviour using direct and indirect trust recommendations received from neighbour nodes. The detection rate of misbehaving nodes is less during the initial life of the network. Therefore we propose a method that detects the node misbehaviour during the initial life by using a multi-hop acknowledgement system. The simulation results show that the proposed method performs well in detecting the gray-hole and node misbehaviour. <br>
Molecular cloning and functional characterization of factors involved in post-transcriptional gene expression.

Messenger RNA is formed from precursors known as pre-mRNA. Theseprecursors associate with proteins to form pre-mRNA-protein(pre-mRNP) complexes. Processing machines cap, splice and polyadenylatethe pre-mRNP and in this way build the mRNP. These processingmachines also affect the export of the mRNP complexes from thenucleus to the cytoplasm. Export to the cytoplasm takes placethrough a structure in the nuclear membrane called the nuclearpore complex (NPC). Export involves adapter proteins in themRNP and receptor proteins that bind to the adapter proteinsand to components of the NPC. We show that the export receptorchromosomal region maintenance protein 1 (CRM1), belonging toa family of proteins known as importin-s-like proteins,binds to gene-specific Balbiani ring (BR) pre-mRNP while transcriptiontakes place. We also show that the GTPase known as Ran bindsto BR pre-mRNP, and that it binds mainly in the interchromatin.However, we also show using leptomycin B treatment that a NES-CRM1-RanGTPcomplex is not essential for export, even though both CRM1 andRan accompany the BR mRNP through the NPC. Our results thereforesuggest that several export receptors associate with BR mRNPand that these receptors have redundant functions in the nuclearexport of BR mRNP.
Use of Triamcinolone to Reduce the Inflammation Associated with Kybella Injection

Background: Submental fullness has been a concern for patients in dermatology for years. Liposuction and cosmetic surgery were considered the mainstay for elimination of unwanted submental fat. However, these procedures are invasive and associated with major complications like prolonged recovery times, and the risk of contour irregularities. In 2015, Kybella (deoxycholic acid) was approved as a first-in-class injectable agent for the treatment of submental fullness. Although, it is non-invasive and has less complications than plastic surgery, it is still associated with adverse effects such as pain, swelling/edema, and bruising. The most concerning adverse effect for patients is the prolonged inflammation that may occur for up to 2 weeks post-injection. Objective: This is a comparison trial of deoxycholic acid injections with or without triamcinolone acetate for the reduction of submental fat in one patient. The study will also assess the effect of triamcinolone acetate on post-injection inflammation associated with deoxycholic acid injection in the treatment of submental fullness. Method: A 35-year-old female presented for evaluation of submental fullness and opted for treatment with Kybella. Her right submental treatment area was injected with 2ml of deoxycholic acid 10mg/ml plus 0.2ml triamcinolone acetate. The left submental treatment area was treated with 2ml of deoxycholic acid 10mg/ ml alone. The patient was observed over a duration of 3 months to evaluate inflammation and treatment response between the two treatment zones. Results: This split-neck study resulted in decreased postinjection swelling. However, at 3-month follow-up, there was no clinical improvement to the submental fullness bilaterally. Limitations: Small sample size, lack of objective measures, possible diffusion between treatment zones, and prior deoxycholic acid treatment. Conclusion: Triamcinolone can decrease post-injection swelling if given as an adjunct to Kybella treatment.
Redes neurais densamente conectadas para detecção de câncer de mama em imagens histopatológicas

Mesmo com todos os avancos das tecnologias medicas, o câncer continua sendo um dos maiores responsaveis por morte no mundo. Nas mulheres o câncer de mama e o segundo câncer com mais incidencia, se diagnosticado precocemente pode ser curado. Um dos procedimentos de diagnosticos e a biopsia, que produz uma imagem que deve ser analisada atraves de um microscopio por um patologista. Com o grande avanco da visao computacional e aprendizado profundo, e possivel fazer com que computadores auxiliarem medicos para uma melhor taxa de diagnosticos corretos, com as experiencias dos medicos e o poder computacional das maquinas que hoje se tem. Pode-se melhorar a qualidade de vida de pessoas que sofrem desta enfermidade fazendo um diagnostico mais preciso e precoce. A DenseNet e uma arquitetura de redes neurais apresentadas em 2017 por Huang et al. (2017) que surgiram destes avancos, visando um melhor desempenho tem um padrao de conexao nunca antes vistos entre as camadas, lida muito bem com o problema da dissipacao do gradiente e requer menos parâmetros. Este trabalho apresenta os conceitos chaves, tecnicas e implementacoes para que esse objetivo em relacao a medicina seja alcancado, sera utilizado aprendizado profundo, redes neurais e processamento de imagem os quais mostraram a viabilidade de tal pratica aplicada na medicina para reconhecer imagens de biopsias dos seios que contenham câncer. Foram feitas classificacoes binarias e multi classes.
Détermination du portage nasal de Staphylococcus aureus chez les étudiants de la faculté de médecine de Tizi-Ouzou et impact du microbiote des non porteurs sur la culture des souches de portage

Staphylococcus aureus is a Gram-positive bacterium, opportunistic pathogen of humans and various mammals. About one third of the population are carriers of S.aureus mostly housed in the nostrils. Nasal colonization is a major risk factor for infection. The starting point of this work was to perform a nasal swab for student medical school volunteers to identify the species S. aureus, then study the sensitivity of isolated strains to antibiotics, and finally the influence of human microbiota of non-carriers on the carriage of S.aureus. 108 subjects were recruited, 54,6% were nasal carriers of S. aureus, with a frequency of 90% of MRSA, and this high rate can be justified by the narrow age range, almost all the medical sciences students who constitute the essential part of our sample.
Social Media Mining for Ideation by using Classification Methods

Ideation is the most crucial and the first step of almost any innovation process [1]. It starts with either identifying a problem or creating a need for any product/service development process. Ideation process can occur within or outside of the organisations’ endeavours. Nowadays, many firms have procedures and software to motivate and collect ideas internally. This is a very common approach for especially large companies as they do have an access to enormous human capital and resources. Considering external resources, open innovation, co-creation or crowdsourcing are popular concepts and approaches where companies interact with consumers, inventors and other organisations to enhance their innovation capability. One of the most popular process in all open external approaches is to gather information from consumers for different stages of the innovation process. Many companies have structured systems, methods and targeted competitions to obtain valuable inputs from consumers about their existing products or potential innovations. One innovative approach and a cost-effective alternative to collect ideas from external resources could be based on a social media data such as Twitter, Facebook and Instagram. Social media is a great source to mine data especially if the required information is about consumers and products. Twitter is
Review On Technologies For Antimicrobial Testing Methods For Veterinary Origin

Antimicrobial Susceptibility Testing (AST) is gaining importance in medical practice as the patients are to be treated with correct Antibiotic with appropriate dosage. For humans one to one communication between the doctor, patient and instrumentation will helps the doctor for the diagnosis but in the case of animals only traditional methods are used for diagnosis and the antibiotics are used randomly, which causes the death of the animals and unnecessary deposition of Antibiotic in the Animal Body. In the case of the humans Isolation and identification of the organisms are important but in the case of animals identification of the right antibiotic in right dosage in less time is important. For the penetration of the systems to the remote location to the farmer’s automation of the systems is the best solution to reduce the experimentation and costs. As there is necessity for resistance surveillance, the zone readers and automated broth dilution system are widely used due to its quantative results and electronic data management. The selection for an AST technique would be based on several factors such as minimal effort of procedure, flexibility, ablity to adapt for automatic system s, expense, robustness and precision.Although slow, the standard methods used for the AST are precise.This review paper summarizes standard techni ques of AST, optical strategies, mechanical methods, semiautomated methods, and fully automated techniques.Techniques currently were using, focusin g on a few hopeful evolving but also coming years technologies in the area of fast profiling of antibiotic susceptibility.
Safely Managing Data Variety in Big Data Software Development

We consider the task of building Big Data software systems, offered as software-as-a-service. These applications are commonly backed by NoSQL data stores that address the proverbial Vs of Big Data processing: NoSQL data stores can handle large volumes of data and many systems do not enforce a global schema, to account for structural variety in data. Thus, software engineers can design the data model on the go, a flexibility that is particularly crucial in agile software development. However, NoSQL data stores commonly do not yet account for the veracity of changes when it comes to changes in the structure of persisted data. Yet this is an inevitable consequence of agile software development. In most NoSQL-based application stacks, schema evolution is completely handled within the application code, usually involving object mapper libraries. Yet simple code refactorings, such as renaming a class attribute at the source code level, can cause data loss or runtime errors once the application has been deployed to production. We address this pain point by contributing type checking rules that we have implemented within an IDE plug in. Our plug in ControVol statically type checks the object mapper class declarations against the code release history. ControVol is thus capable of detecting common yet risky cases of mismatched data and schema, and can even suggest automatic fixes.
Merging Approaches to Explore Connectivity in the Anemonefish, Amphiprion bicinctus, along the Saudi Arabian Coast of the Red Sea

To investigate population genetic patterns of the anemonefish Amphiprion bicinctus in the Red Sea, we isolated and characterized 35 microsatellite loci using 454sequencing. Microsatellite sequences were identified using the Tandem Repeats Finder program. Out of 100 putative markers, we identified the 35 most polymorphic and reliably scorable loci. The markers were tested on 80 individuals sampled from two spatially separated populations along the Saudi Arabian Red Sea coast. We found a mean of 10.9 alleles per locus and observed levels of heterozygosity ranged from 0.4 to 0.98. All loci were polymorphic, none deviated significantly from Hardy-Weinberg equilibrium, no linkage disequilibrium was observed and there was no evidence for nullalleles in both populations. As an additional test, we assessed within-group pairwise relatedness. The markers reported here constitute the first specific set for this species, and they are expected to contribute to future studies of connectivity in the Red Sea region.
COMP4801 Interim Report Facial Expression Synthesis using Generative Adversarial Network

Facial expression synthesis is the process of rendering face images with target expressions while preserving identity information. The generated images can be used in various areas including aﬀective interaction, data augmentation, artiﬁcial agent, etc. Existing methods are usually conducted in a sequence to sequence manner which requires the availability of a video of varying facial expressions of a subject. However, the lack of such data in real life limits the application of these methods. Synthesizing facial expressions on limited faces remains an open problem. In recent years, the generative adversarial networks (GANs) [5] have received substantial attention. GAN consists of two models: (1) Generator G that produces images based on random noises and (2) Discriminator D that distinguishes fake images rendered by G from real sample images. GAN establishes a minimax adversarial game be-tween G and D, making the generated images look more and more real. Diﬀerent variations of GANs have been applied successfully to age progression/regression [16], image super-resolution [8], image to image translation [7], etc. In this project, we use the idea of GAN to synthesize face images, i.e. given a subject I and a facial expression E, an image with identity I and expression E should be generated. We have proposed a GAN model based on Adaptive Instance Normalization (AdaIN) [13] which enables transfer learning. We have trained it on the public dataset CelebA [9] and observe reasonable results. It can alter face images based on a wide range of expressions in terms of action units, which describe the muscle movements of human faces.