Miracle-dz/UniFAR-FTUs huggingface dataset:
Data transmission for cluster-based wireless sensor networks using SET protocol

Secure data transmission is a critical issue for wireless sensor networks (WSNs). Clustering is an effective and practical way to enhance the system performance of WSNs. In this paper, we study a secure data transmission for cluster-based WSNs (CWSNs), where the clusters are formed dynamically and periodically. We propose two Secure and Efficient data Transmission (SET) protocols for CWSNs. In SET, security relies on the hardness of the Diffie-Hellman problem in the pairing domain. SET protocol is further reduces the computational overhead of protocol security, which is essential for WSNs, while its security relies on the hardness of the discrete logarithm problem. In this Existing System of wireless sensor network comprised of spatially distributed devices using wireless sensor nodes to monitor physical or environmental conditions.
An effective anonymization technique of big data using suppression slicing method

Now a days there is a large collection of information and is being published in public network. This large data may contain personal information of a person. So, a difficulty in publishing the data of an individual to publish it without the information leak. To avoid the identification of an individual, security must be provided. Many anonymization techniques are used for the privacy of personal information. While publishing the data, techniques like anonymization using generalization and slicing failed to prevent membership disclosure and also has a linkage of information. This eventually led to the loss of utility. Slicing technique uses the horizontal and vertical partitioning for a perfect sepapration between the uncorrelated attributes to avoid the privacy exploitation. Suppression slicing has overcome this backlogs by comparing the attributes and tuples for similarity check and hide those data values to avoid the linkage and background attack. Thus an effective suppression slicing method is given, which are performed on the attributes having similar values for better utility and privacy.
THE ROLE OF IL-17 IN THE INNATE IMMUNE RESPONSE TO OROPHARYNGEAL CANDIDIASIS

Oropharyngeal candidiasis (OPC; thrush) is an opportunistic oral infection caused by the commensal fungus Candida albicans that afflicts immunosuppressed and immunocompromised individuals. Although patients with HIV/AIDS are the prototypical population associated with development of thrush, there are a host of conditions that lead to susceptibility to OPC, including Hyper-IgE Syndrome (HIES). The autosomal dominant form of HIES (AD-HIES) is characterized by inherited dominant negative mutations in the STAT3 transcription factor, which is crucial for physiologic homeostasis and development in many tissues, including immune cells. Due to the ubiquitous nature of STAT3, mutations in this gene lead to a highly varied set of clinical sequelae, including oral thrush. Numerous cytokines utilize STAT3 to mediate downstream signaling, including IL-6 and IL-23, which are crucial for the differentiation and expansion of T helper 17 (Th17) cells, respectively. IL-23 is necessary for 1) in vivo expansion of Th17 cells, and 2) the secretion of IL-17 and other proinflammatory cytokines. Recently, the Th17 lineage has been shown to play a major role in host defense against OPC. Our lab has previously shown that mice deficient in the IL-17 receptor (IL-17RAKO) and IL-23p19 (IL-23KO) are susceptible to OPC. Furthermore, saliva from both AD-HIES patients and IL-23KO mice exhibits reduced ability to kill C. albicans ex vivo. However, despite the requirement for both IL-17 and IL-23 in protecting against OPC, we found that CD4-specific STAT3 knockout (CD4(stat3KO)) mice are not susceptible to our model of OPC. These data suggested that STAT3 mediates the initial response to oral C. albicans challenge by inducing an IL-17-producing subset other than Th17. Experiments carried out in this study revealed that the initial source of IL-17 is lymphocytic, and is likely multifactorial, involving both γδ and αβ T cells. Furthermore, in this study, natural killer and natural killer T cells were shown to have no apparent role in IL-17 secretion in response to C. albicans challenge in the oral cavity. In addition, while a memory or rechallenge response may involve CD4+ Th17 cells, this lineage appears to be unessential for the initial response to C. albicans in the oral cavity. Although we also attempted to examine the immune response to OPC using a mouse model of HIES harboring a transgenic STAT3 mutation, these mice proved resistant to C. albicans challenge at the buccal mucosa. However, despite the OPC resistance, they did exhibit a skin phenotype consistent with STAT3 deficiency, including eczematous lesions and delayed wound healing. These findings suggest that this mouse model may be used to study the role of STAT3 in both eczema as well as the immune response to cutaneous Staphylococcus aureus and C. albicans skin infections in the context of STAT3.
Sound ( symbolic ) patterns in Pokémon names : Focusing on voiced obstruents and mora counts

This paper presents a case study of sound symbolism, cases in which certain sounds tend to be associated with particular meanings. The current study uses the corpus of all Pokémon names available as of October 2016. This paper explores the effects of voiced obstruents and mora counts in Japanese Pokémon names, and demonstrates that both of them impact Pokémon characters’ size, weight, strength parameters, and evolution levels. In particular, the number of voiced obstruents in Pokémon names positively correlates with size, weight, evolution levels, and general strength parameters, except for speed. We argue that this result is compatible with the Frequency Code Hypothesis proposed by Ohala (1984, 1994). The number of moras in Pokémon names positively correlates with size, weight, evolution levels and all strength parameters. Multiple regression analyses show that the effects of voiced obstruents and those of mora counts hold independently of one another. Not only does this paper offer a new case study of sound symbolism, it provides evidence that sound symbolism is at work when naming proper nouns. In general, the materials provided in this paper are useful for undergraduate education in linguistics and psychology to attract students’ interests, as Pokémon is very popular among current students.
Can Food Porn Make Us Slim? How Brains of Consumers React to Food in Digital Environments

People constantly publish/share their pictures/videos of delicious food dishes on social media. This excessive display of food pictures on Instagram, Facebook, Twitter, Snapchat, Pinterest, and other social media is often referred to as “food porn”. Seeing food presented in an appetizing and/or “ready to be eaten” manner allows the brains of the viewer to vividly imagine the consumption experience related to eating what they see. Looking at pictures of food is known to trigger gustatory sensations in the brain, and to often triggering the desire to consume. As the food industry is using social media to promote their products, public health prevention and organizations in charge of promoting healthy lifestyles would be behooved to coincide their practices with this digital (r)evolution. This article discusses how multisensory mental simulation – i.e. the imagination of all the sensations associated with food consumption via social media, can be used to produce satiety. In addition, making the consumption of healthy foods more appetizing and enjoyable to better regulate food intake.
Self-healing by property-guided structural adaptation

Self-healing is an increasingly popular approach ensuring resiliency, that is, a proper adaptation to failures, in cyber-physical systems (CPS). A very promising way of achieving self-healing is through structural adaptation (SHSA), by replacing a failed component with a substitute component. We present a knowledge base modeling relations among system variables given that certain implicit redundancy exists in the system and show how to extract a substitute from that knowledge base using guided search. The result of our search, i.e., the substitute, is optimal w.r. t. a user-defined utility function considering properties of the system variables (e.g., accuracy). We demonstrate our approach — Self-Healing by Property-Guided Structural Adaptation (SH-PGSA) — by deploying it in a real-world CPS prototype of a rover whose sensors are susceptible to failure. We further show the increased runtime performance to find the optimal substitute by comparing it to related work.
Chiari II brain malformation : why is it so closely associated with spina bifida ? 2 . Portfolio summary

Aims: Open spina bifida (OSB; ‘myelomeningocele’) is a common cause of neurodisability in young children. However, the most life-threatening aspect of OSB is the Chiari II brain malformation, which affects 90% of OSB cases. A recent, randomised control trial of antenatal versus postnatal repair of myelomeningocele, concluded that antenatal repair resulted in a lower incidence of Chiari II malformation compared with conventional postnatal repair [1]. This observation is the most commonly cited indication for antenatal surgery. This project aims to determine why Chiari II so commonly accompanies SB, as this is not understood. The student will test the following hypothesis, which represents the most prevalent view [2] on Chiari II origin: Hypothesis: Chiari II malformation results primarily from persistent cerebrospinal fluid (CSF) leakage from the OSB lesion in utero, leading to a small hindbrain and reduced posterior skull fossa size which, in turn, causes the cerebellar vermis / brain stem to herniate.
Learning Interval Representations from Polyphonic Music Sequences

Many music theoretical constructs (such as scale types, modes, cadences, and chord types) are defined in terms of pitch intervals---relative distances between pitches. Therefore, when computer models are employed in music tasks, it can be useful to operate on interval representations rather than on the raw musical surface. Moreover, interval representations are transposition-invariant, valuable for tasks like audio alignment, cover song detection and music structure analysis. We employ a gated autoencoder to learn fixed-length, invertible and transposition-invariant interval representations from polyphonic music in the symbolic domain and in audio. An unsupervised training method is proposed yielding an organization of intervals in the representation space which is musically plausible. Based on the representations, a transposition-invariant self-similarity matrix is constructed and used to determine repeated sections in symbolic music and in audio, yielding competitive results in the MIREX task "Discovery of Repeated Themes and Sections".
Performance Guaranteed Control of Flywheel Energy Storage System for Pulsed Power Load Accommodation

Pulsed power load (PPL) consumes a huge amount of energy within a very short period of time. Directly connecting a PPL to a shipboard power system (SPS) will cause large disturbance even instability during PPL deployment. As an important category of energy storage system (ESS), the flywheel ESS (FESS) is an ideal source for PPL accommodation. By powering the PPL separately with a sufficiently charged FESS, the negative impacts of PPL on SPS can be avoided. The paper presents an adaptive output-constrained control design that can realize fast charging of the FESS and simultaneously minimize the disturbance to system frequency. Major benefit of the algorithm is that transient response can be guaranteed to stay within user-defined, time-varying bounds. This property makes the algorithm different from typical adaptive control algorithms and very appealing for high-performance applications. By applying the standard Lyapunov synthesis, all closed-loop signals are proved to be bounded. Finally, the proposed control design is tested through simulations using SPS models with different details. Simulation results demonstrate the effectiveness of the proposed control design.
The association between cholesterol levels and brachial/aortic augmentation index versus cognitive status in patients with cardiovascular risk factors

Cardiovascular pathology appears to have a major impact in cognitive decline, and early identification and correction of cardiovascular morbidity could have a major protective impact on cognitive functioning. However, it is not clear how the risk factors for vascular disease can also be risk factors for a general cognitive decline. Regarding cholesterol, its implications in cognitive decline are not very well understood, considering that a high level of cholesterol has been associated with both an increased and decreased risk of dementia. In the present context, we decided to study correlations between cholesterol concentration and the various subdomains of some main psychometric tests, such as MMSE (Mini-Mental State Examination) and MoCA (The Montreal Cognitive Assessment), as well as some measurements for systemic arterial stiffness (brachial and aortic augmentation index) and how they correlate with the aforementioned psychometric parameters. Our results provide additional evidence for a correlation between cholesterol levels and cognitive subdomains (with special focus on orientation, attention, recent memory and long-term memory). Additionally, a significant correlation was found between the brachial and aortic augmentation index and the results of both MMSE and MOCA tests.
Plaque‐induced gingivitis: Case definition and diagnostic considerations

OBJECTIVE Clinical gingival inflammation is a well-defined site-specific condition for which several measurement systems have been proposed and validated, and epidemiological studies consistently indicate its high prevalence globally. However, it is clear that defining and grading a gingival inflammatory condition at a site level (i.e. a "gingivitis site") is completely different from defining and grading a "gingivitis case" (GC) (i.e. a patient affected by gingivitis), and that a "gingivitis site" does not necessarily mean a "GC". The purpose of the present review is to summarize the evidence on clinical, biochemical, microbiologic, genetic markers as well as symptoms associated with plaque-induced gingivitis and to propose a set of criteria to define GC. IMPORTANCE A universally accepted case definition for gingivitis would provide the necessary information to enable oral health professionals to assess the effectiveness of their prevention strategies and treatment regimens; help set priorities for therapeutic actions/programs by health care providers; and undertake surveillance. FINDINGS Based on available methods to assess gingival inflammation, GC could be simply, objectively and accurately identified and graded using bleeding on probing score (BOP%) CONCLUSIONS: A patient with intact periodontium would be diagnosed as a GC according to a BOP score ≥ 10%, further classified as localized (BOP score ≥ 10% and ≤30%) or generalized (BOP score > 30%). The proposed classification may also apply to patients with a reduced periodontium, where a GC would characterize a patient with attachment loss and BOP score ≥ 10%, but without BOP in any site probing ≥4 mm in depth.
Influence of Knowledge Transfer and Knowledge Conversion on Performance of Commercial Banks in Kenya

This study examines the influence of knowledge transfer and knowledge conversion on performance of Commercial Banks in Kenya. The study adopted explanatory and cross-sectional survey design. The target population of this study comprised of all the 43 Commercial Banks in Kenya. The unit of observation was the functional area in each bank. Primary data was collected using a semi-structured questionnaire. The questionnaire was hand delivered and collected later by the researcher in order to enhance the response rate. Secondary data was collected using document review and was used to validate information collected from the questionnaire. The response rate in this study was approximately seventy three percent which was considered adequate for making inferences and drawing conclusions. Quantitative data was analyzed using descriptive and inferential statistics. Descriptive statistics included percentages, frequencies, means, and standard deviations while inferential statistics involved regression analysis. Results from quantitative data analysis were presented using figures and tables. The findings of the study established that knowledge conversion and knowledge transfer have positive influence on performance.
A Supercritical Fluids Extraction Process for the Production of Drug Loaded Biodegradable Microparticles

The purpose of this thesis was to develop methods suitable for the incorporation of drug substancessuch as proteins into microparticles intended for controlled release. In particular a novel techniquefor the preparation of microparticles using supercritical fluids was investigated.Supercritical fluids offer a considerable promise as extraction media for the formation ofmicroparticles of drugs and pharmaceutical excipients. There are two main reasons for using this technique. Firstly, the selective solvating power of supercritical fluids makes it possible to separatea particular component from a multi-component mixture. Secondly, the favourable mass transfer properties and high solubility of solvent in supercritical fluid make the formation of the microparticles rapid and efficient. The Solution Enhanced Dispersion by Supercritical fluids process (SEDS) was used for the production of microparticles from several different biodegradable polymers. Briefly, particles were formed by the extraction of solvent from a solution which was sprayed into a supercritical fluid. The use of a combination of supercritical N2 and CO2 in the SEDS process, improved the dispersion of polymer solutions, as compared with CO2 alone. This resulted in reduction of the particle size of discrete microparticles produced from amorphous biodegradable polymers. Proteins (lysozyme and urease) were successfully incorporated into the poly(d,l-lactide-co-glycolide): copolymer composition 50:50 (DL-PLG) microparticles. The particles showed high entrapment efficiencies and the incorporated proteins retained a high degree of biological activity. Compared with conventional technologies for the preparation of such drug delivery systems, e.g. solvent-evaporation emulsion techniques, this new technique is environmentally superior, and suitable for up-scaling. Moreover the higher degree of control as indicated by the high reproducibility, makes validation of the process feasible. In conclusion, the SEDS process is an attractive way of incorporating proteins and peptides into biodegradable microparticles for controlled release.
Towards tight approximation bounds for graph diameter and eccentricities

Among the most important graph parameters is the Diameter, the largest distance between any two vertices. There are no known very efficient algorithms for computing the Diameter exactly. Thus, much research has been devoted to how fast this parameter can be approximated. Chechik et al. [SODA 2014] showed that the diameter can be approximated within a multiplicative factor of 3/2 in Õ(m3/2) time. Furthermore, Roditty and Vassilevska W. [STOC 13] showed that unless the Strong Exponential Time Hypothesis (SETH) fails, no O(n2−ε) time algorithm can achieve an approximation factor better than 3/2 in sparse graphs. Thus the above algorithm is essentially optimal for sparse graphs for approximation factors less than 3/2. It was, however, completely plausible that a 3/2-approximation is possible in linear time. In this work we conditionally rule out such a possibility by showing that unless SETH fails no O(m3/2−ε) time algorithm can achieve an approximation factor better than 5/3. Another fundamental set of graph parameters are the Eccentricities. The Eccentricity of a vertex v is the distance between v and the farthest vertex from v. Chechik et al. [SODA 2014] showed that the Eccentricities of all vertices can be approximated within a factor of 5/3 in Õ(m3/2) time and Abboud et al. [SODA 2016] showed that no O(n2−ε) algorithm can achieve better than 5/3 approximation in sparse graphs. We show that the runtime of the 5/3 approximation algorithm is also optimal by proving that under SETH, there is no O(m3/2−ε) algorithm that achieves a better than 9/5 approximation. We also show that no near-linear time algorithm can achieve a better than 2 approximation for the Eccentricities. This is the first lower bound in fine-grained complexity that addresses near-linear time computation. We show that our lower bound for near-linear time algorithms is essentially tight by giving an algorithm that approximates Eccentricities within a 2+δ factor in Õ(m/δ) time for any 0<δ<1. This beats all Eccentricity algorithms in Cairo et al. [SODA 2016] and is the first constant factor approximation for Eccentricities in directed graphs. To establish the above lower bounds we study the S-T Diameter problem: Given a graph and two subsets S and T of vertices, output the largest distance between a vertex in S and a vertex in T. We give new algorithms and show tight lower bounds that serve as a starting point for all other hardness results. Our lower bounds apply only to sparse graphs. We show that for dense graphs, there are near-linear time algorithms for S-T Diameter, Diameter and Eccentricities, with almost the same approximation guarantees as their Õ(m3/2) counterparts, improving upon the best known algorithms for dense graphs.
Enantioselective Enzymatic Naphthoyl Ring Reduction.

Birch reductions of aromatic hydrocarbons by means of single-electron-transfer steps depend on alkali metals, ammonia, and cryogenic reaction conditions. In contrast, 2-naphthoyl-coenzyme A (2-NCoA) and 5,6-dihydro-2-NCoA (5,6-DHNCoA) reductases catalyze two two-electron reductions of the naphthoyl-ring system to tetrahydronaphthoyl-CoA at ambient temperature. Using a number of substrate analogues, we provide evidence for a Meisenheimer complex-analogous intermediate during 2-NCoA reduction, whereas the subsequent reduction of 5,6-dihydro-2-NCoA is suggested to proceed via an unprecedented cationic transition state. Using vibrational circular dichroism (VCD) spectroscopy, we demonstrate that both enzymatic reductions are highly stereoselective in D2 O, providing an enantioselective pathway to products inaccessible by Birch reduction. Moreover, we demonstrate the power of VCD spectroscopy to determine the absolute configuration of isotopically engendered alicyclic stereocenters.
Multi-objective clustering and routing for maximizing lifetime of wireless sensor networks

Multi-objective optimization is a technology of multiple criteria decision making, which is suitable for routing and clustering in wireless sensor networks (WSNs). In WSNs, clustering need to consider nodes' energy, the distance to the cluster heads (CHs), etc. Additionally, routing need to consider nodes' energy and the hops to the base station (BS), etc. However, existing algorithms just consider some of the factors or convert multiple factors into a single objective function resulting in worse performances. In this paper, an improved non-dominated sorting particle swarm optimizer for multi-objective optimization (INSPSO) is proposed to prolong network lifetime. We also adopt a non-uniform clustering strategy to avoid hot spot problem caused by multi-hop communication. Then, we simulate the proposed algorithm and compare with some existing clustering and routing algorithms to demonstrate the advantages of our algorithm.