Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization techniques to improve lifetime of wireless sensor networks: A review

Currently wireless sensor networks (WSN) are finding wide range of applications when integrated with Internet of things (IoT). WSNs contain sensor nodes which are tiny, battery operated devices. Therefore resource management in wireless sensor network is one of the significant research issues in improving the lifetime of the sensor network. Several optimization techniques have been proposed in this direction to improve life-time of WSN. In this paper, we are proposing a novel approach to address the resource management problem with respect to energy parameter which can considerably increase the network lifespan. Whenever a network is deployed for a specific application, the performance parameters that are considered for evaluation are data-redundancy, sleep-awake cycle, buffering mechanism, architectural-design, etc. This paper discusses the application of bio-inspired, Jumper Firefly Algorithm which optimizes network lifetime through centralized clustering and dynamic routing algorithm.
Intake of Lactobacillus reuteri Improves Incretin and Insulin Secretion in Glucose-Tolerant Humans: A Proof of Concept

OBJECTIVE Ingestion of probiotics can modify gut microbiota and alter insulin resistance and diabetes development in rodents. We hypothesized that daily intake of Lactobacillus reuteri increases insulin sensitivity by changing cytokine release and insulin secretion via modulation of the release of glucagon-like peptides (GLP)-1 and -2. RESEARCH DESIGN AND METHODS A prospective, double-blind, randomized trial was performed in 21 glucose-tolerant humans (11 lean: age 49 ± 7 years, BMI 23.6 ± 1.7 kg/m2; 10 obese: age 51 ± 7 years, BMI 35.5 ± 4.9 kg/m2). Participants ingested 1010 b.i. d. L. reuteri SD5865 or placebo over 4 weeks. Oral glucose tolerance and isoglycemic glucose infusion tests were used to assess incretin effect and GLP-1 and GLP-2 secretion, and euglycemic-hyperinsulinemic clamps with [6,6-2H2]glucose were used to measure peripheral insulin sensitivity and endogenous glucose production. Muscle and hepatic lipid contents were assessed by 1H-magnetic resonance spectroscopy, and immune status, cytokines, and endotoxin were measured with specific assays. RESULTS In glucose-tolerant volunteers, daily administration of L. reuteri SD5865 increased glucose-stimulated GLP-1 and GLP-2 release by 76% (P < 0.01) and 43% (P < 0.01), respectively, compared with placebo, along with 49% higher insulin (P < 0.05) and 55% higher C-peptide secretion (P < 0.05). However, the intervention did not alter peripheral and hepatic insulin sensitivity, body mass, ectopic fat content, or circulating cytokines. CONCLUSIONS Enrichment of gut microbiota with L. reuteri increases insulin secretion, possibly due to augmented incretin release, but does not directly affect insulin sensitivity or body fat distribution. This suggests that oral ingestion of one specific strain may serve as a novel therapeutic approach to improve glucose-dependent insulin release.
Antimicrobial susceptibilities of Lactobacillus, Pediococcus and Lactococcus human isolates and cultures intended for probiotic or nutritional use.

OBJECTIVES To determine MICs of 16 antimicrobials representing all major classes for 473 taxonomically well-characterized isolates of lactic acid bacteria (LAB) encompassing the genera Lactobacillus, Pediococcus and Lactococcus. To propose tentative epidemiological cut-off (ECOFF) values for recognizing intrinsic and acquired antimicrobial resistances in numerically dominant species. METHODS On the basis of depositors' information, LAB were grouped in categories of probiotic, nutritional, probiotic or nutritional research, human and animal isolates and tested for their antibiotic susceptibilities by broth microdilution using LAB susceptibility test medium (LSM). Tentative ECOFFs were defined according to the recommendations of the European Committee on Antimicrobial Susceptibility Testing. Isolates showing acquired antimicrobial resistance(s) were selected for PCR-based detection of resistance gene(s) and in vitro conjugative transfer experiments. RESULTS Tentative ECOFF values of 13 antibiotics were determined for up to 12 LAB species. Generally, LAB were susceptible to penicillin, ampicillin, ampicillin/sulbactam, quinupristin/dalfopristin, chloramphenicol and linezolid. LAB exhibited broad or partly species-dependent MIC profiles of trimethoprim, trimethoprim/sulfamethoxazole, vancomycin, teicoplanin and fusidic acid. Three probiotic Lactobacillus strains were highly resistant to streptomycin. Although erythromycin, clindamycin and oxytetracycline possessed high antimicrobial activities, 17 Lactobacillus isolates were resistant to one or more of these antibiotics. Eight of them, including six probiotic and nutritional cultures, possessed erm(B) and/or tet(W), tet(M) or unidentified members of the tet(M) group. In vitro intra- and interspecies filter-mating experiments failed to show transfer of resistance determinants. CONCLUSIONS Finding of acquired resistance genes in isolates intended for probiotic or nutritional use highlights the importance of antimicrobial susceptibility testing in documenting the safety of commercial LAB.
Performance Evaluation of Service-Oriented Architecture using Generalized Stochastic Petri Net

oriented architecture (SOA) is a software architecture design pattern based on discrete pieces of software providing application functionality as services to other applications. Before application of SOA, if a model of problem is drawn and analyzed, then possible flaws in architecture implementation phase could be prevented. This paper presents a method for evaluating SOA based on formal models. To achieve this goal, products of C4ISR framework are calculated, then are marked on UML diagrams to get the real model. For this purpose, the UML elements should be indexed according to efficiency. Following that the UML elements based on presented algorithm are transformed to GSPN. The results suggest that the ATM is done on a case study demonstrates that modeling and evaluation in the design phase prevents the high cost of implementation phase. Keywords-Oriented Architecture, Non-Functional Requirement, Software Architecture, Performance Evaluation, Formal Model.
Effects of land cover change on temperature and rainfall extremes in multi-model ensemble simulations

Abstract. The impact of historical land use induced land cover change (LULCC) on regional-scale climate extremes is examined using four climate models within the Land Use and Climate, IDentification of robust impacts project. To assess those impacts, multiple indices based on daily maximum and minimum temperatures and daily precipitation were used. We contrast the impact of LULCC on extremes with the impact of an increase in atmospheric CO2 from 280 ppmv to 375 ppmv. In general, consistent changes in both high and low temperature extremes are similar to the simulated change in mean temperature caused by LULCC and are restricted to regions of intense modification. The impact of LULCC on both means and on most temperature extremes is statistically significant. While the magnitude of the LULCC-induced change in the extremes can be of similar magnitude to the response to the change in CO2, the impacts of LULCC are much more geographically isolated. For most models, the impacts of LULCC oppose the impact of the increase in CO2 except for one model where the CO2-caused changes in the extremes are amplified. While we find some evidence that individual models respond consistently to LULCC in the simulation of changes in rainfall and rainfall extremes, LULCC's role in affecting rainfall is much less clear and less commonly statistically significant, with the exception of a consistent impact over South East Asia. Since the simulated response of mean and extreme temperatures to LULCC is relatively large, we conclude that unless this forcing is included, we risk erroneous conclusions regarding the drivers of temperature changes over regions of intense LULCC.
Tubular D-branes in Salam-Sezgin model

We study DBI-type effective theory of an unstable D3-brane in the background manifold 1,1 × 2 where 2 is an arbitrary two-dimensional manifold. We obtain an exact tubular D2-brane solution of arbitrary cross sectional shape by employing 1/cosh tachyon potential. When 2 = S2, the solution is embedded in the background geometry 1,3 × S2 of Salam-Sezgin model. This tachyon potential shows a unique property that an array of tachyon soliton solutions has a fixed period which is independent of integration constants of the equations of motion. The thin BPS limit of the configurations leads to supertubes of arbitrary cross sectional shapes.
Dept. for Speech, Music and Hearing Quarterly Progress and Status Report Perception of Question Intonation and Facial Gestures Perception of Question Intonation and Facial Gestures

This paper presents results from two perception experiments designed to investigate intonational cues and visual facial cues to interrogative mode in Swedish. Results from the intonation test indicate that both a widened F0 range on a final focal accent and time alignment properties of the F0 rise and peak make important contributions to the interrogative percept. Results from the audiovisual test showed that vertical head nodding and smiling tended to reinforce declarative intonation. Interrogative intonation, however, was not strengthened by hypothesized interrogative visual cues consisting of eyebrow movement and slow vertical head movement. The interaction between audio and visual cues for accentuation and interrogative mode is discussed and some implications of adding the visual modality to the traditional definition of question intonation are explored.
The Effect of Gold and Iron-Oxide Nanoparticles on Biofilm-Forming Pathogens

Microbial biofilms on biomaterial implants or devices are hard to eliminate by antibiotics due to their protection by exopolymeric substances that embed the organisms in a matrix, impenetrable for most antibiotics and immune-cells. Application of metals in their nanoparticulated form is currently considered to resolve bacterial infections. Gold and iron-oxide nanoparticles are widely used in different medical applications, but their utilisation to eradicate biofilms on biomaterials implants is novel. Here, we studied the effect of gold and iron oxide nanoparticles on Staphylococcus aureus and Pseudomonas aeruginosa biofilms. We report that biofilm growth was reduced at higher concentrations of gold and iron-oxide nanoparticles compared to absence of nanoparticles. Thus nanoparticles with appropriate concentration could show significant reduction in biofilm formation.
Clinical Implications of Changing Parameters on an Elliptical Trainer

Background: Specific weightbearing instructions continue to be a part of routine orthopaedic clinical practice on an injured or postoperative extremity. Researchers and clinicians have struggled to define the best weightbearing strategies to maximize clinical outcomes. Purpose: To investigate the average percentage body weight (APBW) values, weightbearing distribution percentages (WBDP), and cadence values on the entire foot, hindfoot, and forefoot during changing resistance and incline on an elliptical trainer, as well as to suggest clinical implications. Study Design: Descriptive laboratory study. Methods: An original research study was performed consisting of 30 asymptomatic subjects (mean age, 29.54 ± 12.64 years; range, 21-69 years). The protocol included 3 consecutive tests of changing resistance and incline within a speed range of 70 to 95 steps/min. The SmartStep weightbearing gait analysis system was utilized to measure the values. Results: The APBW values for the entire foot ranged between 70% and 81%, the hindfoot values were between 27% and 57%, and the forefoot values between 42% and 70%. With regard to WBDP, the forefoot remained planted on the pedal (stance phase) 2 to 3 times more as compared with the hindfoot raise in the swing phase. Conclusion: The study findings highlight the fact that elliptical training significantly reduces weightbearing in the hindfoot, forefoot, and entire foot even at higher levels of resistance and incline. Clinical Relevance: Weightbearing on the hindfoot consistently displayed the lowest weightbearing values. Orthopaedic surgeons, now equipped with accurate weightbearing data, may recommend using the elliptical trainer as a weightbearing exercise early on following certain bony or soft tissue pathologies and lower limb surgical procedures.
Communities Putting Prevention to Work: Results of an Obesity Prevention Initiative in Child Care Facilities

ABSTRACT Obesity is a significant public health issue affecting even our youngest children. Given that a significant amount of young children are enrolled in child care, the goal of this project was to evaluate the effectiveness of a child care facility-based obesity prevention program. Over 1,000 facilities participated in the study. The intervention consisted of teacher trainings and technical assistance focused around the implementation of four policies: snack, beverage, physical activity, and screen time. Changes in teacher’s attitudes and beliefs, as well as improvements in healthy lifestyle practices, were assessed. Results revealed significant improvements in child care center practices, such as: (1) the amount of health-related lessons provided to students increased t(664) = −6.09, P < 0.00; (2) the amount of outdoor physical activity increased t(702) = −3.83, P < 0.000; (3) the amount of screen time decreased t(686) = −2.52, P < 0.01; (4) the amount of juice served decreased t(577) = −7.38, P < 0.000; and (5) the amount of junk food decreased t(568) = −2.73, P < 0.006. The findings from this study can be easily disseminated and potentially serve as a model for improving the quality of nutrition and physical activity practices in child care facilities.
Fuzzy Handling of Continuous-Valued Attributes in Decision Trees

Classical crisp decision trees (DT) are widely applied to classiication tasks. Nevertheless, there are still a lot of problems especially when dealing with numerical (continuous-valued) attributes. Some of those problems can be solved using fuzzy decision trees (FDT). This paper proposes a method for handling continuous-valued attributes with automatically generated (as opposed to user deened) membership functions. An example will be given at the end. The aim of this paper is to combine decision trees (DT) with fuzziness, i.e. to use fuzziness to solve problems in the eld of DT. Most real-world applications of classiication learning involve continuous-valued attributes. However, Top Down Induction of Decision Tree (TDIDT) Qui86] algorithms only use nominal attributes. Therefore continuous-valued attributes have to be discretized before they are selected, typically by partitioning the range of the attribute into subranges. In principle, a discretization is simply a logical condition (using one or more attributes) that serves to partition the data into at least two subsets. The main question is where to set the so-called cut points to partition the numerical attributes. Fayyad and Irani FI92a] FI92b] suggested a method for selecting the cut point as the midpoint between each successive pair of attribute values which has later been improved by the same authors and by Seidelmann Sei93]. The base for the algorithm are logical conditions like "A(x) < T", which means: a threshold T is determined and the test A(x) < T is assigned to the left branch while A(x) T is assigned to the right branch. Further investigations tried to reduce the number of cut points (boundary points) that always separate two classes FI93]. By using entropy (as known from the construction of decision trees Qui86]) these boundaries decide whether such a point separates the attribute values having maximum information gain (cut point). While constructing the decision tree, algorithms do not only have to nd the testing attribute for each node, but also the "best" separation of this attribute. Moreover, Fayyad and Irani FI93] generalize the method and show that the separation is not necessarilly binary. In our opinion, there is one weak point in the method sketched above: the ""nal" position of the cut points is exactly halfway between two numerical attribute values. Unseen examples that have to be classiied later might be near to this threshold value and therefore classiied incorrectly. A possible way to overcome this diiculty is handling the numerical attributes …
Peer-to-Peer Rating

This paper proposes to utilize algorithms from the probabilistic graphical models domain for Peer-to-Peer rating of data items and for computing "social influence" of nodes in a Peer-to-peer social network. We evaluate the practicality of our approach using large- scale simulations over a MSN Live Messenger subgraph consisting of about a million nodes. Our algorithms are general since they can be used for Peer-to-peer monitoring and for the efficient computation of other node ranking methods, such as PageRank and Information Centrality.
CUSTOMER CHURN PREDICTION USING LOCAL LINEAR MODEL TREE FOR IRANIAN TELECOMMUNICATION COMPANIES

For winning in global competition, companies need to recognition and monitoring of customer's behavior to forecast their behavior and desires earlier than competitors. This research tries to recognize the attributes which lead to customer churn. For this, behavior of 3150 subscribers of an Iranian mobile operator, has observed during one year and trends of them has analyzed by a customized LLNF model. For this purpose, the application of the locally linear model tree (LOLIMOT) algorithm, which integrates the advantage of neural networks, tree model and fuzzy modeling, was experimented. Results suggest that dissatisfaction of customer, his/her usage from services and demographic attributes have significant effect on decision to churn or retention. Furthermore, the active or inactive subscriber situation has mediation effect on his/her retention.
EARTHQUAKE DESTRUCTION ASSESSMENT OF URBAN ROADS NETWORK USING SATELLITE IMAGERY AND FUZZY INFERENCE SYSTEMS

: The idea of assessing the damages to roads network after earthquake strikes has been referred as a matter of importance for performing every systematically planned activity in the affected region. When gathering information about the devastated region is crucially costly and time-consuming and in most cases impossible, high-resolution satellite imagery is hired to provide fast and accurate information for every assessment and evaluation processes. Therefore, this research is mainly focused on design and development of a method to evaluate the damages to the roads network, using pre-event digital vector map and post-event high-resolution satellite imagery. In this case, using pre-event digital vector map and post-event satellite imagery, the roads network is extracted and then processed for determination of road blocks across city roads network. The existence of many violating objects at the scene of satellite imagery may mislead the process of finding blocked roads. Therefore, violating objects are detected and removed through Fuzzy engines. Then, analyzing the spectral and textural properties and comparing specific computed set of descriptors, the damage and no-damage objects are marked. Through inspecting the results, hiring Fuzzy Inference Systems, the blocked road sections in the region are detected. The proposed method is evaluated using digital vector map and QuickBird Pan-sharpened images of the city of Bam, located southwest of Iran regarding to the devastating earthquake in December 2003. The visual inspections have confirmed the capabilities of the method for evaluation urban road network after earthquake strikes.
SOFTWARE ARCHITECTURE FOR MULTIPLE DOMAIN DIALOGUE SYSTEM

In this paper we propose multiple domain dialogue system (MDDS), a system possessing knowledge of many domains, enables user to interact with the computer system in their natural language. We have also presented the software architecture for describing the top-level design of MDDS. The functional components of this system are realized and the software architecture of the system is designed and conceived in various levels of abstraction. Index terms – Software architecture, Dialogue System, Language Technology
The Structure of Locally Compact Approximate Groups

Author(s): Carolino, Pietro Kreitlon | Advisor(s): Tao, Terence C | Abstract: A subset A of a locally compact group G is said to be a K-approximate group if it contains the identity, is closed under inverses, and if the product set AA = {ab | a,b \in A} can be covered by K left-translates of A. In this work we prove a structure theorem on open precompact K-approximate groups that describes them as a combination of compact subgroups, convex sets in Lie algebras of dimension bounded in terms of K, and certain generalizations of arithmetic progressions. Our results can naturally be regarded as generalizations of a theorem of Breuillard, Green, and Tao that describes finite approximate groups, and also of a theorem of Gleason and Yamabe, which describes locally compact groups as inverse limits of Lie groups.Along the way we prove continuous analogues of additive combinatorial results of Sanders, Croot, and Sisask, and model-theoretic results of Hrushovski, all of which were first obtained in the finite context.
Oncomirs: The potential role of non-coding microRNAs in understanding cancer

MicroRNAs (miRNAs) are members of a family of non-coding RNAs of 8-24 nucleotide RNA molecules that regulate target mRNAs. The first miRNAs, lin-4 and let-7, were first discovered in the year 1993 by Ambros, Ruvkun, and co-workers while studying development in Caenorhabditis elegans. miRNAs can play vital functions form C. elegans to higher vertebrates by typical Watson-Crick base pairing to specific mRNAs to regulate the expression of a specific gene. It has been well established that multicellular eukaryotes utilize miRNAs to regulate many biological processes such as embryonic development, proliferation, differentiation, and cell death. Recent studies have shown that miRNAs may provide new insight in cancer research. A recent study demonstrated that more than 50% of miRNA genes are located in fragile sites and cancer-associated genomic regions, suggesting that miRNAs may play a more important role in the pathogenesis of human cancers. Exploiting the emerging knowledge of miRNAs for the development of new human therapeutic applications will be important. Recent studies suggest that miRNA expression profiling can be correlated with disease pathogenesis and prognosis, and may ultimately be useful in the management of human cancer. In this review, we focus on how miRNAs regulate tumorigenesis by acting as oncogenes and anti-oncogenes in higher eukaryotes.