Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanisms of non-canonical NF-kappaB regulation

NF-kappaB is activated through two signaling cascades: the classical and non-canonical pathways, which are distinguished based on the Inhibitor of kappaB Kinase (IKK) components required to activate each pathway. Whereas classical NF-kappaB requires NF-kappaB Essential Modulator (NEMO) and IKKbeta, noncanonical NF-kappaB requires IKKalpha and upstream stabilization of NF-kappaB Inducing Kinase (NIK), but not NEMO. However, we have previously shown that IKKalpha contains a functional NEMO binding domain and associates with NEMO and IKKbeta as part of the heterotrimeric IKK complex. The overarching goal of the work described in this thesis was to determine whether the interaction between NEMO and IKKalpha was required for non-canonical NF-kappaB signaling. We used a reconstitution approach in knockout cells to show that IKKalpha, independent of its association with NEMO, is sufficient to control the non-canonical NF-kappaB pathway. Thus we provide biochemical evidence to support the tenet that IKKalpha alone regulates non-canonical NF-kappaB signaling. Importantly, while pursuing these results we made the surprising finding that NEMO, and furthermore, IKKbeta, play a compulsory role in the constraint of basal non-canonical NF-kappaB activity. These studies reveal that the previous model depicting a NEMOindependent non-canonical NF-kappaB signaling cascade is incomplete. We show that an intact and catalytically competent classical IKK complex constrains basal NIK accumulation. This novel mechanism of non-canonical NF-kappaB regulation requires classical NF-kappaB transcription driven by the prototypic NFkappaB family member p65. Thus classical NF-kappaB activity is essential to maintain the quiescent state of the non-canonical NF-kappaB signaling pathway. Upon activation, the duration of non-canonical signaling is controlled by a recently described negative feedback mechanism that promotes NIK turnover. We used a combination of translation and proteasome inhibitors to show that turnover of active NIK is proteasomedependent. Furthermore, we utilized a Smac mimetic compound to show that degradation of active NIK does not require cellular inhibitor of apoptosis (cIAP)1/2, which distinguishes this feedback mechanism from the cIAP1/2-dependent mechanism of basal NIK turnover. Collectively, these studies advance our understanding of a recently described mechanism of non-canonical NF-kappaB down-regulation and reveal a novel interplay between classical and non-canonical NF-kappaB activity, which revises the current model of non-canonical NF-kappaB signaling. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Immunology First Advisor Michael J. May
A Novel Approach towards Patient Centric Clinical Decision Support System by using Naive Bayesian Classification based on Cloud Computing

: In the today’s world of digitalization large amount of data getting generated from health care industry. For making proper decision using advanced data mining techniques that helps clinician to make proper decisions, Clinical decision support system is important. Clinical decision support system improves diagnosis accuracy and reduces diagnosis time. As the clinical data is of very large amount for performing any operation on it, some data mining techniques needs to be used. Here, to improve Clinical decision support system, navie bayesian classification algorithm can be utilized to extract useful information. CDSS is promising still it is facing many challenges including information security and privacy concerns. In this paper, We describe patient health related document generation and integration open API service based on cloud computing ,through which hospitals are conveniently generate a patient health related document without having to purchase any proprietary software. It propose a privacy-preserving patient-centric clinical decision support system by using encryption and data mining techniques. Historical data of past patients can be used to train the naive Bayesian classifier without leaking any individual patient data. This will helps clinician to diagnose risk of patient's disease.
From grand design to change on the ground: going to scale with a global feeding strategy.

In May 2002, the World Health Organization (WHO) adopted the Global Strategy for Infant and Young Child Feeding (WHO 2003a). This marked the culmination of a complex process, which included WHO’s methodical consultation of the governments of its then entire membership of 191 governments, solicitation of inputs from an array of other interested parties (including health professional bodies, individual experts, non-governmental organisations, and commercial enterprises and their associations), extensive review of the scientific literature, and technical consultations on crucial topics such as the optimal duration of exclusive breastfeeding (WHO 2001a) and prevention of mother-to-child transmission of human immunodeficiency virus (HIV) (WHO 2001b). As with any global WHO policy instrument, far from being a one-size-fits-all approach, governments were urged to adapt the Global Strategy to the specific circumstances of their nutrition and child health policies and programmes (WHO 2002a). Indeed, for a volume that seeks to shed light on the exceedingly complex challenge of appropriately translating international public health recommendations in multiple culturally diverse settings, the Global Strategy eloquently illustrates the adage ‘Think globally, act locally’. This dimension is all the more evident given the idiosyncratic nature of nurturing and nourishing children based on the rules imposed by the group into which each of us is born. Perhaps the ultimate paradox in this connection is that there can be no universal approach to ensuring unhindered access to our species’ only example of a universal food and feeding system – breast milk and breastfeeding – which are forever mediated by culture and clan. Starting in early 2000, WHO and the United Nations Children’s Fund (UNICEF) began jointly developing the Global Strategy, whose aim is to improve – through optimal feeding – the nutritional status, growth and development, and health, and thus the very survival of infants and young children. Its specific objectives are (WHO 2003a):
Comparing Anodic Bubble Behavior of Anodes from Anisotropic and Isotropic Cokes in Laboratory Scale Aluminum Electrolysis Cells

12 During production of aluminum in Hall-Héroult cells, carbon anodes electrochemically oxidize to form 13 mainly CO2. The CO2 bubbles block the anode working surface during growth and coalescence, leading 14 to cell voltage loss and voltage oscillations. Lower grade isotropic petroleum cokes are currently being 15 introduced to anodes worldwide, but little is known about effects of coke quality on the unavoidable 16 voltage losses linked to bubble formation. To investigate this, a pilot carbon anode series was made 17 with various blended ratios of isotropic to anisotropic coke. The anodes were characterized with 18 respect to voltage oscillations related to bubble formation and release, wettability towards electrolyte 19 and surface roughness before and after electrolysis. Results showed that voltage noise caused by gas 20 bubbles was reduced for anodes containing isotropic coke. For blended anodes of isotropic and 21 anisotropic coke, the potential oscillation amplitude was reduced by ~0.19 V compared to a 100 % 22 anisotropic coke anode. The percentage of the anode surface screened by gas bubbles was also 23 reduced as isotropic coke was introduced. Increased wettability between electrolyte and two anodes 24 containing isotropic coke was observed after anode polarization. The reduced bubble screening on the 25 anode surface was attributed to better wetting between anode and electrolyte. 26
Vulnerabilities Detection via Static Taint Analysis

Due to huge amounts of code in modern software products, there is always a variety of subtle errors or flaws in programs, which are hard to discover during everyday use or through conventional testing. A lot of such errors could be used as a potential attack vector if they could be exploited by a remote user via manipulation of program input. This paper presents the approach for automatic detection of security vulnerabilities using interprocedural static taint analysis. The goal of this study is to develop the infrastructure for taint analysis applicable for detection of vulnerabilities in C and C++ programs and extensible with separate detectors. This tool is based on the Interprocedural Finite Distributive Subset (IFDS) algorithm and is able to perform interprocedural, context-sensitive, path-insensitive analysis of programs represented in LLVM form. According to our research it is not possible to achieve good results using pure taint analysis, so together with several enhancements of existing techniques we propose to supplement it with additional static symbolic execution based analysis stage, which has path-sensitivity and considers memory region sizes for filtering results found by the first stage. The evaluation of results was made on Juliet Test Suite and open-source projects with publicly known vulnerabilities from CVE database.
Specialization in the iStar2.0 Language

iStar2.0 has been proposed as a standard language for building goal- and agent-oriented models. It is an evolution of the former i<sup>*</sup> language, with the purpose of homogenising existing syntactical and semantic variations of basic i<sup>*</sup> constructs that researchers in the field introduced along the years. In its first version (2016), iStar2.0 was intentionally kept simple, and some constructs were merely introduced but not formally defined. One of them is the notion of specialization. The specialization relationship is offered by iStar2.0 through the <monospace>is-a</monospace> construct defined over actors (subactor <inline-formula> <tex-math notation="LaTeX">$x$ </tex-math></inline-formula> <monospace>is-a</monospace> superactor <inline-formula> <tex-math notation="LaTeX">$y$ </tex-math></inline-formula>). Although the overall meaning of this construct is highly intuitive, its semantics when it comes to the fine-grained level of the models is not defined in the standard. In this paper we provide a formal definition of the specialization relationship ready to be incorporated into a next release of the iStar2.0 standard language. We root our proposal over existing work on conceptual modeling in general, and object-orientation in particular. Also, we use the results of a survey that provides some hints about what definition do iStar2.0 modelers expect from specialization. As a consequence of this twofold analysis, we identify, define and specify a set of specialization operations that can be applied over iStar2.0 models. Correctness conditions for them are also formally stated. The result of our work is a formal proposal of specialization for iStar2.0 that allows its use in a well-defined manner and contributes to its standardization.
Studies on the Escherichia coli stringent response protein, RelA

RelA is a guanosine tetraphosphate synthetase which catalyzes the production of (p)ppGpp during the stringent response in Escherichia coli. RelA consists of an Nterminus, which is responsible for the catalytic activity, and a C-terminus, which is thought to be involved in the regulation of RelA activity. Furthermore, the C-terminus has dimerization and ribosome binding ability. ‘RelA-2, which is a fragment of Cterminus, is a major domain responsible for dimerization and ribosome binding. In this study, it was demonstrated that combination of two mutations (C612G, D637R) in ‘RelA-2 significantly reduced the dimerization. This dimerizationdefective mutant still bound to ribosomes both in vivo and in vitro, indicating that dimerization is not required for its ribosome binding and that the dimerizaton domain is separated from its ribosome binding domain. The overexpression of the dimerization-defective mutant in amino acid starved cells inhibited chromosomeencoded wild type RelA activity. As a result, the starved cells did not show a stringent response. This finding does not support the oligomerization model proposed by Gropp group. Previous studies in this laboratory have shown, and were confirmed here, that the overexpressed ‘RelA-3, another fragment of C-terminus, which is devoid of dimerization and ribosome binding ability, did not inhibit the RelA activity when cells are under amino acid starvation. This evidence supports the hypothesis that ribosome binding is somehow involved in the regulation of RelA activity. iv It was demonstrated in this study that RelA was localized to the 50S subunit in vivo by Western Blot analysis. This result confirmed a previous study showing that the 50S subunit had the enzymatic activity in vitro, but not the 30S subunit. However, an in vitro study using pure 50S and 30S ribosomal subunits for the binding experiments indicated that RelA mainly bound to the 30S subunit and weakly to the 50S subunit. A model has been proposed to explain the possible mechanism of ribosome association for RelA. The involvement of L11 and EF-G in the regulation of RelA activity was also investigated. Three residues (C38, G131, and G137) in L11 have been identified to be crucial for the regulation of RelA activity. Three residues (T89, L438, and G628) in EF-G have been identified to be involved in the regulation of RelA activity. These preliminary studies implicate that the regulation of RelA inside amino acid-starved E. coli is complex.
Does University Class Size Matter? Evidence from Course Micro Data

Using the data from macroeconomics test scores and students’ basic information, we estimate class size and average test scores for undergraduate students in Qingdao University of Technology. We find a substantial class size effect. That is, given the two different class sizes---the medium size and the large size, the test score in the medium class size is two scores higher than that of the latter, so to speak, the smaller class size effect is more pronounced. Our finding is consistent with those of others concerning the relationship between class size effect and test scores. Incidentally, science major might enhance score compared to economics major. For policy maker and university administration, this is especially meaningful in terms of the match of classroom resources and students’ course enrollment, as well as teacher assignment or hiring. Keywords—class size; final test scores; Chinese ordinary universities; macroeconomics; micro data
A suitable role : professional identity and nursing in India

This dissertation examines the careers and collective professional identity of nurses working in India. It analyses the impact of gender, caste and class on the decision to enter nursing, the types of career opportunities envisaged by nurses, accounts of nursing practice in hospital settings and the professionalizing strategies debated by the profession's leaders to achieve greater social and professional legitimacy for Indian nurses. The backdrop to this study is the city of Bangalore, a quintessential example of an increasingly globalized India, commonly referred to as the country's 'Silicon Valley'. Bangalore is the site of numerous hospitals and medical facilities and has the largest concentration of nursing educational institutions in the country. As modern, urban India is increasingly characterized by the unravelling of traditional forms of social stratification, the study examines social change within the profession of nursing and its repercussions for the professional identity of nurses. The research draws upon literature from the sociology of professions as a theoretical framework and examines the relevance of these theories to the study setting so as to develop new understandings of nursing culture in a non-Western context. The findings of the study include evidence of a 'collectivist' rather than an 'individualistic' approach to career decision-making in which the presence of 'nurse families' and community networks serve as important social and professional resources. Given the traditional associations with nursing and low status work, the study demonstrates how the professional project of nursing is focused around achieving collective social mobility. The dissertation discusses the importance of migration as a professional 'asset' and highlights contemporary debates around further education and specialization as strategies to achieve greater social and economic rewards for Indian nurses.
An Augmented Reality System to Support Fault Visualization in Industrial Robotic Tasks

The digitalization is transforming the very nature of factories, from automated systems to intelligent ones. In this process, industrial robots play a key role. Even if repeatability, precision and velocity of the industrial manipulators enable reaching considerable production levels, factories are required to face an increasingly competitive market, which requires being able to dynamically adapt to different situations and conditions. Hence, facilities are moving toward systems that rely on the collaboration between humans and machines. Human workers should understand the behavior of the robots, placing trust in them to properly collaborate. If a fault occurs on a manipulator, its movements are suddenly stopped for security reasons, thus workers may not be able to understand what happened to the robot. Therefore, the operators’ stress and anxiety may increase, compromising the human-robot collaborative scenario. This work fits in this context and it proposes an adaptive Augmented Reality system to display industrial robot faults by means of the Microsoft HoloLens device. Starting from the methodology employed to identify which virtual metaphors best evoke robot faults, an adaptive modality is presented to dynamically display the metaphors in positions close to the fault location, always visible from the user and not occluded by the manipulator. A comparison with a non adaptive modality is proposed to assess the effectiveness of the adaptive solution. Results show that the adaptive modality allows users to recognize faults faster and with fewer movements than the non adaptive one, thus overcoming the limitation of the narrow field-of-view of the HoloLens device.
Diagnostic value of immunohistochemistry for the detection of the BRAF(V600E) mutation in papillary thyroid carcinoma: comparative analysis with three DNA-based assays.

BACKGROUND The aim of this study was to compare the detection of BRAF(V600E) by immunohistochemistry (IHC) using a mutation-specific antibody with molecular biology methods for evaluation of papillary thyroid carcinoma (PTC) patients. PATIENTS AND METHODS This study concerned 198 consecutive conventional PTC patients, of which the majority were women (133/198; 67%), with a mean age of 56 years (range 19-79 years). BRAF mutation analysis was performed using DNA-based (direct sequencing, pyrosequencing, and SNaPshot) and IHC (VE1 antibody) methods. The sensitivity and specificity of IHC for BRAF(V600E) was compared with the molecular biology data. RESULTS A BRAF mutational result was obtained in 194 cases. A BRAF(V600E) mutation was detected in 153/194 (79%) cases of PTC when using at least one molecular method, and in 151/194 (78%) cases with IHC. No false positive results were noted using IHC to detect the BRAF(V600E) mutation. Besides this mutation, other rare BRAF mutations (BRAF(V600K) and BRAF(K601E)), used as negative controls, were consistently negative with IHC. The sensitivity and specificity of IHC for the detection of this mutation were 98.7% and 100% respectively. The IHC test demonstrated excellent performance at a level equivalent to two DNA-based counterparts (pyrosequencing and SNaPshot). Failure to achieve a result was more frequent with the direct sequencing method than with the three other methods. CONCLUSION IHC using the VE1 antibody is a specific and sensitive method for the detection of the BRAF(V600E) mutation in PTC. IHC may be an alternative to molecular biology approaches for the routine detection of this mutation in PTC patients.
Exploiting Particle Swarm Optimization to Attune Strong Fuzzy Partitions Based on Cuts

Cut-based strong fuzzy partitions (SFP) are characterized by cuts, i.e. points in the universe of discourse where the non-zero membership degrees of the fuzzy sets in the partition is 0.5. Cuts are useful to identify the most representative regions for the fuzzy sets involved in a SFP but pose loose constraints on the slopes of trapezoidal fuzzy sets. We address the problem of optimizing such slopes in order to maximize the performance of fuzzy rule-based systems while keeping cuts constant. This way, model performance is improved and interpretability is preserved. We use Particle Swarm Optimization to perform optimization and we analyze two different approaches for generating solution spaces. We tested the proposed approach on a number of fuzzy rule-based classifiers designed by DC* (Double Clustering with A*) on synthetic data. For all the considered models, performance is never degraded but improved in many cases, without violating any interpretability constraint.
Initial Rotor Position Detection for Brushless DC Motors Based on Coupling Injection of High-Frequency Signal

In applications where motor inversion is forbidden, it is important to detect the initial rotor position of the motor. For this reason, based on coupling injection of high-frequency signal, a novel method of initial rotor position detection for brushless DC motors (BLDCM) is proposed in this paper. Firstly, the proposed method detects the relationship between three-phase winding inductances by injecting the high-frequency detection signal into motor windings in a coupling way, and the initial rotor position is determined into two sectors with 180 degrees electric angle difference. Then, the polarity of the permanent magnet rotor is determined by applying two opposite voltage vectors to motor windings, so that the initial rotor position is determined into a unique sector, and the positioning accuracy is 30 degrees electric angle. The proposed method significantly reduces the amplitude of the detection signal while increases its frequency by the way of coupling injection, thus reducing the response current and electromagnetic torque generated by the high-frequency signal and reducing the possibility of rotor inversion. Finally, the effectiveness of the proposed method is verified by experimental results.
Dynamic Trajectory Planning and Tracking for Autonomous Vehicle With Obstacle Avoidance Based on Model Predictive Control

In this study, an obstacle avoidance controller based on nonlinear model predictive control is designed in autonomous vehicle navigation. The reference trajectory is predefined using a sigmoid function in accordance with road conditions. When obstacles suddenly appear on a predefined trajectory, the reference trajectory should be adjusted dynamically. For dynamic obstacles, a moving trend function is constructed to predict the obstacle position variances in the predictive horizon. Furthermore, a risk index is constructed and introduced into the cost function to realize collision avoidance by combining the relative position relationship between vehicle and obstacles in the predictive horizon. Meanwhile, lateral acceleration constraint is also considered to ensure vehicle stability. Finally, trajectory dynamic planning and tracking are integrated into a single-level model predictive controller. Simulation tests reveal that the designed controller can ensure real-time trajectory tracking and collision avoidance.