Chemical Modification on Gold Slides to Gain Better Control of Patterning Techniques

Nanolithography is a rapidly evolving field that requires new combinations of techniques to improve patterning and to assist in fabricating electromechanical devices. An increasing number of applications require surfaces with defined regions of different chemical functionality. In our previous project optimum conditions for lithographic patterning were determined and potential blockers were identified to reduce force on the tip. This work is focused on identifying good chemical modifications that will allow better control of basic patterning and to investigate the minimum force of patterning required while using each chemical system. The primary aim is to gain better control of basic pattern techniques in order to create more intricate patterns such as interdigitated arrays, which can subsequently be used in sensors. An atomic force microscope (AFM) is used to pattern the prepared colloid-coated glass slides. Several compounds were used in the investigation, including sodium sulphate, potassium sulphate, magnesium sulphate, sodium fluoride, sodium chloride, sodium bromide, and sodium iodide, potassium chloride, potassium bromide, potassium iodide, potassium dihydrogen phosphate, and potassium hydrogen phosphate. In Summary, the following were found as a result of this work: The groups of sulphates were determined to require minimum patterning forces as indicated. Sodium sulphate took a force of 49 n Potassium sulphate took a force of 45 nN Magnesium sulphate took a force of 744.4 nN The group of sodium and potassium halides were determined the minimum patterning forces as indicated. Sodium fluoride took a force of 8.42 nN Sodium chloride and potassium chloride took a force of 20.19 and 61.9nN Sodium bromide and potassium bromide took a force of 601.4 nN and 37.2 nN, respectively Sodium iodide and potassium iodide took a force of 953.7 nN and 47.2 nN, respectively The phosphates were determined to require the minimum patterning forces as indicated. Potassium hydrogen phosphate took a force of 25nN Potassium dihydrogen phosphate took a force of 43 n

The effect of glucose on osteoblast differentiation

Diabetic or hyperglycemic patients have an increased propensity towards fracture and the skeletal healing process is highly ineffective with delayed healing or non-unions. This is attributed to the accumulation of Advanced Glycation End-products (AGEs) on proteins due to a glycosylation reaction that occurs when greater levels of sugars are present. The subsequent stress caused by the AGEs results in an improper osteoblast differentiation that leads to higher susceptibility to osteopenia and bone fracture. The periosteum is the most important source of progenitor skeletal cells because the cells contained here are the ones that have the most potential to differentiate into chondrocytes and osteoblasts. Thus, the layer of connective tissue that the periosteum provides is a necessary part of an effective fracture healing process. Much research has been conducted regarding the bone-marrow derived cells and their role in the skeletal repair process and osteogenesis for diabetic patients. However, mechanisms regarding the effect of diabetes and hyperglycemia on the periosteum and its role in assisting with bone regeneration as well as the role of AGEs in the progenitor stem cells involved in fracture repair have yet to be elucidated. Therefore, the primary objective of this thesis to determine the effect of glucose on osteoblast differentiation using three sources of progenitor cells: the periosteum, the bone marrow and muscle tissue

The role of autophagy in cartilage physiology and metabolism : implications for growth and ageing

Cartilage is the main constituent of the embryonic skeleton. At the ends of long bones cartilage forms a growth plate consisting of chondrocytes in distinct stages of differentiation and arranged into three zones. These chondrocytes mediate linear bone growth through synchronized proliferation, differentiation, and production of matrix. The cartilage lining the articulating surfaces of bones also contains chondrocytes arranged in different layers that secrete extracellular matrix and preserve cartilage integrity. Articular cartilage is relatively permanent, whereas the growth plate is transient. Although each of these cartilaginous structures has a unique structure and function, one fundamental similarity is that the chondrocytes in both are exposed to little blood and, thereby, low levels of oxygen and nutrients. Autophagy is an intracellular pathway of lysosomal degradation that protects cells from both internal and external stressors and promotes cell viability when nutrition is limited. The protein kinase mTORC1 is a negative regulator of autophagy and its activity is, in turn, governed by various stimuli such as nutrition and growth factors, depletion of which inhibits mTORC1 and activates autophagy. Attenuated autophagy leads to various developmental and ageing-associated degenerative diseases. Therefore, our primary hypothesis was that autophagy promotes chondrocyte survival, so, that inhibition of this process may impair the linear growth of bones and promote the development of agerelated osteoarthritis. Our second hypothesis was that autophagy improves metabolic parameters during long-term intermittent caloric restriction. First, we studied the role of autophagy in the chondrocytes of mouse metatarsal bones and in C5.18 cells by blocking this process with the lysosomal inhibitors bafilomycin A1 and chloroquine. We found that mTORC1 activity in chondrocytes was increased by blocking lysosomal V-ATPase enzymes. This effect is chondrocyte-specific and in contrast to well-accepted dogma. At the same time, inhibition of lysosomal activity stimulated the linear growth of mouse metatarsal bones by enhancing chondrocyte hypertrophy. Moreover, chondrocytes with impaired autophagy showed similar responses (Paper I). Subsequently, to investigate the effects of autophagy on linear bone growth (Paper II) and ageassociated osteoarthritis (Paper III) directly we abrogated autophagy in chondrocytes by conditional deletion of the autophagy related Atg5 or Atg7 gene. We observed reduced axial and appendicular bone growth due to attenuated chondrocyte proliferation and elevated cell death in both cases. Moreover, chondrocyte viability in the human growth plate and mouse metatarsal bones was reduced by treatment with 3-methyladenine or bafilomycin A1, inhibitors of autophagy (Paper II). Fibrillations and proteoglycan loss in the articular cartilage of aged mice without a functional Atg5 gene was elevated indicating the development of osteoarthritis (Paper III). These impaired bone growth and degenerative changes in articular cartilage are the consequences of enhanced apoptosis mediated by activation of caspases-3 and -9 (Paper II and III). Furthermore, release of cytochrome C initiated the cleavage of caspases even in the absence of autophagy (Paper II). Finally, we examined the role of autophagy in metabolism during intermittent caloric restriction (according to a 5:2 diet) in obese individuals and with and without type II diabetes. We observed improvements in anthropometric and metabolic parameters in both our diabetic and non-diabetic subjects. Moreover, in diabetic subjects whose insulin sensitivity was improved by caloric restriction, autophagy also increased (Paper IV). In conclusion, the observations from our in vitro and in vivo studies confirm that autophagy is essential for the survival and homeostasis of chondrocytes in the growth plate and articular cartilage. At the same time, mTORC1 activation is chondrocyte-specific and independent of autophagy. In addition, autophagy improves metabolic parameters during intermittent caloric restriction in humans. Elucidating mTOR induced autophagy in greater detail will provide further insights in to disorders of linear growth, cartilage degeneration and metabolism, there by opening up novel approaches to treatment

Karma: Resource Allocation for Dynamic Demands

The classical max-min fairness algorithm for resource allocation provides many desirable properties, e.g., Pareto efficiency, strategy-proofness and fairness. This paper builds upon the observation that max-min fairness guarantees these properties under a strong assumption -- user demands being static over time -- and that, for the realistic case of dynamic user demands, max-min fairness loses one or more of these properties. We present Karma, a generalization of max-min fairness for dynamic user demands. The key insight in Karma is to introduce "memory" into max-min fairness -- when allocating resources, Karma takes users' past allocations into account: in each quantum, users donate their unused resources and are assigned credits when other users borrow these resources; Karma carefully orchestrates exchange of credits across users (based on their instantaneous demands, donated resources and borrowed resources), and performs prioritized resource allocation based on users' credits. We prove theoretically that Karma guarantees Pareto efficiency, online strategy-proofness, and optimal fairness for dynamic user demands (without future knowledge of user demands). Empirical evaluations over production workloads show that these properties translate well into practice: Karma is able to reduce disparity in performance across users to a bare minimum while maintaining Pareto-optimal system-wide performance.Comment: Accepted for publication in USENIX OSDI 202

A Survey of Deep Learning Approaches for Natural Language Processing Tasks

In recent years, deep learning has been a go-to method for solving difficult NLP problems. Deep learning models have attained state-of-the-art performance across a wide range of natural language processing applications, including text summarization, sentiment analysis, named entity identification, and language translation, by utilizing enormous neural network designs and massive volumes of training data. In this paper, we take a look at the most important deep learning methods and how they've been used for different natural language processing jobs. We go over the basics of neural network designs including CNNs, RNNs, and transformers, and we also go over some of the more recent developments, such as BERT and GPT-3. Our discussion of each method centers on its guiding principles, benefits, drawbacks, and significant NLP applications. To further illustrate the relative merits of various models, we also provide their comparative performance findings on industry-standard benchmark datasets. We also highlight some of the present difficulties and potential future avenues of study in deep learning applied to natural language processing. The purpose of this survey is to offer academics and practitioners in natural language processing a high-level perspective on how to make good use of deep learning in their respective fields

OPTIC NEUROPATHY INDUCED BY LOW DOSE OF ETHAMBUTOL: A RARE PRESENTATION

Ethambutol is a bacteriostatic antimicrobial agent used in the treatment of tuberculosis. Optic neuropathy is a potentially severe side effect of ethambutol, which is dose related. Ethambutol-induced optic neuropathy (EON) incidence is 15%, 5% & 1% when taken at 50 mg/kg/day , 25 mg/kg/day & 15 mg/kg/day respectively for 3 months. We report a case of bilateral EON in 20-year-old female after 1 month of exposure to 15 mg/kg/day of ethambutol for tubercular meningitis. Ophthalmologic examination revealed bilateral ill sustained pupillary reactions and optic disc pallor. Deranged color vision test and scotomas on Goldmann perimetry in both eyes, aided in diagnosis.Keywords: Low dose ethambutol, Optic neuropathy, Tuberculosis

SHORTSTACK : Distributed, Fault-tolerant, Oblivious Data Access

Many applications that benefit from data offload to cloud services operate on private data. A now-long line of work has shown that, even when data is offloaded in an encrypted form, an adversary can learn sensitive information by analyzing data access patterns. Existing techniques for oblivious data access—that protect against access pattern attacks—require a centralized and stateful trusted proxy to orchestrate data accesses from applications to cloud services. We show that, in failure-prone deployments, such a centralized and stateful proxy results in violation of oblivious data access security guarantees and/or in system unavailability. We thus initiate the study of distributed, fault-tolerant, oblivious data access. We present SHORTSTACK , a distributed proxy architecture for oblivious data access in failure-prone deployments. SHORTSTACK achieves the classical obliviousness guarantee—access patterns observed by the adversary being independent of the input—even under a powerful passive persistent adversary that can force failure of arbitrary (bounded-sized) subset of proxy servers at arbitrary times. We also introduce a security model that enables studying oblivious data access with distributed, failure-prone, servers. We provide a formal proof that SHORTSTACK enables oblivious data access under this model, and show empirically that SHORTSTACK performance scales near-linearly with number of distributed proxy servers

Stratification of, albeit Artificial Intelligent (AI) Driven, High-Risk Elderly Outpatients for priority house call visits - a framework to transform healthcare services from reactive to preventive

House calls have nostalgic view and have practiced decades ago when the doctor arrived at the patient's door carrying a big black bag. House calls could prove to be a better way of treating very sick, elderly patients while they can still live at home. One of the greatest benefits is avoidance of Healthcare associated infections. Additionally, house calls save time and energy of immediate care members of and helps seek for ways to have transport for elderly. A house calls doctor, nonetheless, can see only five to seven patients a day. One reason is that a house call visit can take longer than an office visit, even after taking travel time into account. One way of optimizing house call delivery services is to employ AI based system to identify and generate priority list so that the healthcare providers have greater coverage of their needed patients house calls are performed in-time. In this paper, we propose innovative novel idea “AI enabled house calls are best medicine practices for the next generation”. Finally, as part of the paper, we will present Sanjeevani house call service that is been deployed and currently in productio