Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel cannabinoid CB 2 receptor-selective inverse agonist blocks leukocyte recruitment in vivo

The expression of the cannabinoid CB 2 receptor on peripheral immune cells suggests that compounds specific for CB 2 might be effective anti-inflammatory agents. In this report we present the initial biological profiling of a novel triaryl bis-sulfone, Sch.336 which is selective for the human cannabinoid CB 2 receptor (hCB 2 ). Sch.336 is an inverse agonist at hCB 2 , as shown by its ability to decrease GTP γ S binding to membranes containing hCB 2 , by the ability of GTP γ S to left-shift Sch.336 binding to hCB 2 in these membranes, and by the compound’s ability to increase forskolin-stimulated cAMP levels in CHO cells expressing hCB 2 . In these systems, Sch.336 displays a greater potency than that reported for the CB 2 -selective dihydropyrazole SR144528. In vitro, Sch.336 impairs the migration of CB 2 -expressing recombinant cell lines to the cannabinoid agonist 2-arachidonylglycerol. In vivo, the compound impairs migration of cells to cannabinoid agonist HU210. Oral administration of the Sch.336 significantly inhibited leukocyte trafficking in several rodent in vivo models, induced either by specific chemokines or by antigen challenge. Finally, oral administration of Sch.336 blocked ovalbumin-induced lung eosinophilia in mice, a disease model for allergic asthma. We conclude that selective cannabinoid CB 2 inverse agonists may serve as novel immunomodulatory agents in the treatment of a broad range of acute and chronic inflammatory disorders in which leukocyte recruitment is a hallmark of disease pathology. 2005). Here we demonstrate that Sch.336 effectively blocks the migration of cells in response both to the cannabinoid agonist 2-arachidonylglycerol in vitro, and to more complex chemotactic signals in vivo. We show that oral administration of Sch.336 significantly impairs leukocyte trafficking in three diverse models of inflammation. These data suggest that the cannabinoid CB 2 receptor plays a critical role in leukocyte recruitment to sites of inflammation and indicates that CB 2 -selective inverse agonists may provide a novel immunotherapeutic treatment of inflammatory diseases.
Symplectic circle actions with isolated fixed points

Consider a symplectic circle action on a closed symplectic manifold with non-empty isolated fixed points. Associated to each fixed point, there are well-defined non-zero integers, called weights. We prove that the action is Hamiltonian if the sum of an odd number of weights is never equal to zero (the weights may be taken at different fixed points). Moreover, we show that if $\dim M=6$, or if $\dim M=2n \leq 10$ and each fixed point has weights $\{\pm a_1, \cdots, \pm a_n\}$ for some positive integers $a_i$, it is enough to consider the sum of three weights. As applications, we recover the results for semi-free actions, and for certain circle actions on six-dimensional manifolds.
Integrating Internet of Things (IoT) in the Measurements and Instrumentation Course

Mohammad Habibi is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Wisconsin-Platteville. Prior to coming to the UW-Platteville, he was an assistant professor of Integrated Engineering at Minnesota State University-Mankato. He earned his Ph.D. degree in Electrical Engineering from the University of Wisconsin-Milwaukee in 2010. His primary research interests are in the field of signal processing, dielectric spectroscopy, and sensors. Specifically, he is interested in developing novel medical devices. In addition to his technical research, he is also an active member of the American Society of Engineering Education (ASEE) and conducts research in engineering education.
Collision-Free Indoor Navigation Using an Artificial Potential Field Controller

Path planning is the problem of finding a collision-free path from a mobile agent’s initial position to its goal position, and moving the agent along that path. This Master’s thesis presents a control algorithm based on artificial potential fields for navigating a mobile agent in indoor environments. An artificial potential field is a scalar field defined in the environment of the agent, whose intensity relates to objects in the environment and the goal of the agent. The gradient of the scalar field is a vector field and determines the motion of the agent. The proposed algorithm produces control vectors that move the agent in an indoor environment towards its goal position. Collision with obstacles is quantified probabilistically, and the resulting quantity called the probability of collision is used to adapt the potential fields. Localization is a necessary step for calculating the probability of collision and the control vectors. Anchor nodes with known positions in the environment provide measurement information necessary for localization. The agent performs range measurements relative to the anchor nodes, and its position is estimated by a cubature Kalman filter from observed data. The probability of collision is used to adapt the artificial potential field such that within the framework of our approximation of the true probability of collision, the resulting control vector attempts to keep the probability of collision under a threshold. Simulations show that the proposed algorithm enables the agent to navigate indoor environments without collisions in various scenarios. In the absence of local minima between the initial and goal positions of the agent, a path is easily found with little to no adaptation of the fields. The algorithm also shows some capability for escaping from and avoiding local minima.
The contribution of at-home and away-from-home food to dietary intake among 2–13y Mexican children

Objectives— Away-from-home foods have been shown to have lower nutritional quality and larger portion sizes as compared to many foods prepared at home. The objective of this study was to describe calorie and nutrient intakes among 2–13y old Mexican children by eating location (at-home and away-from-home), overall, by socio-economic status (SES), and by urbanicity. Design— Dietary intake was collected via one 24-hr recall in the 2012 Mexican National Health and Nutrition Survey (ENSANUT). Location was reported for each food consumed. Results were adjusted for age, sex, weight status, socio-economic status and urbanicity. Results— majority of daily home 82%, respectively). The most common away-from-home eating location was the school (22% 2–5y; 43% 6–13y old), followed by street (14% 2–5y; 13% 6–13y old). The most common foods consumed away-from-home were wheat, rice, and corn mixed dishes, and sugar-sweetened beverages (SSBs), pastries/ candy/desserts, milk (2–5y only) and salty snacks (6–13y). Multivariate models showed that high SES 2–5 year-olds consumed 14% of daily energy away-from-home relative to 8% among low SES 2–5 year-olds, and high SES 6–13 year-olds consumed 21% of daily energy away-from-home compared to 14% among low SES 6–13 year-olds. There were no differences by urban residence. Conclusions— Among Mexican children, most foods and beverages were consumed at home. However, the percent of foods consumed or purchased away-from-home increased with age and with SES.
Genotyping Neisseria gonorrhoeae Using Fluorescent Ampliﬁed Fragment Length Polymorphism Analysis

An evaluation of ﬂuorescent ampliﬁed fragment length polymorphism (FAFLP) for typing Neisseria gonor- rhoeae using 52 isolates revealed that its discriminatory power approached that of Opa-typing in identifying epidemiologically linked isolates. Automated, accurate sizing of FAFLP ampliﬁed fragments permits objective data analysis and storage, making it an attractive method for large surveillance projects. Elucidating relationships between isolates of Neisseria gonorrhoeae can contribute to the identiﬁcation of outbreaks and sexual networks, the recognition of temporally or geographi-cally predominant strains, and the monitoring of antibiotic resistance. Auxotyping and serotyping are commonly applied to N. gonorrhoeae and can serve as a preliminary screen of heterogeneity. Combined auxotype/serovar classiﬁcation im-proves resolution but does not always distinguish between epidemiologically related and unrelated isolates (16). Molecular typing methods meet the need for higher resolution (3, 5, 10, 13, 14, 16, 18, 19, 22). Of these, Opa-typing (16), pulsed-ﬁeld gel electrophoresis (18–20), and sequencing of the entire por gene (3) currently give the best discrimination between strains of N. gonorrhoeae (23). Sequencing of the
Locality-aware load-balanced task scheduling for MapReduce (cid:73)

Task scheduling for MapReduce jobs has been an active area of interest since the popularization of MapReduce framework. The objective of scheduling is to decrease the amount of data transfer during the shuﬄe phase via exploiting data locality. In the literature, generally only the scheduling of reduce tasks is considered with the assumption that scheduling of map tasks is already determined by the input data placement. However, in cloud or HPC deployments of MapReduce, the input data is located in a remote storage and scheduling map tasks gains importance. Here, we propose models for simultaneous scheduling of map and reduce tasks in order to improve data locality and balance the processors’ loads in both map and reduce phases. Our approach is based on graph and hypergraph models which correctly encode the interactions between map and reduce tasks. Partitions on these graphs and hypergraphs are decoded to schedule map and reduce tasks. A two-constraint formulation utilized in these models enables balancing processors’ loads in both map and reduce phases. The partitioning objective in the hypergraph models correctly encapsulates the minimization of data transfer when a local combine step is performed prior to shuﬄe, whereas the partitioning objective in the graph models achieve the same feat when a local combine is not performed. We show the validity of our scheduling on the MapReduce parallelizations of two important kernel operations–sparse matrix-vector multiplication (SpMV) and generalized sparse matrix-matrix multiplication (SpGEMM)–that are widely encountered in big data analytics and scientiﬁc computations. Compared to random scheduling, our models lead to tremendous savings in data transfer in the shuﬄe phase, leading up to 2.6x and 4.2x speedup for SpMV and SpGEMM, respectively.
A study of 3D Password

— The current security systems have weaknesses which can be vulnerable to threat. Textual passwords are commonly used. Users usually choose meaningful words from dictionaries, which make it easy to crack and revealed vulnerable to hacking or brute force attacks. Many graphical passwords have a password space that is less than or equal to textual password scheme. Smart cards or tokens can be lost or stolen. Many biometric authentications have been proposed but some people refuse because of their intrusiveness and effect on their privacy. This paper represents multifactor authentication scheme 3D Password. It include all the types of security schemes Textual, Graphical and many others but users provided option to choose the level of security and user acceptability. More over we provide a 3D virtual environment to navigate and interact with various objects more effectively and productively, The sequence of actions and interactions made by the user towards the objects inside the 3D environment constructs the user's password.
Investigation of Some Cognitive Difficulties in Set Theory

A previous study on students approach to problems of Set Theory in Iran brought me some hypotheses. These encouraged me to test the hypotheses in this supplementary study. My purpose of this study was to consider some students' cognitive difficulties in Set Theory. I investigated students’ conceptual understanding of two major concepts of Set Theory – the concepts of inclusion and belonging. I also studied the ways students use Venn diagram to figure out problems in Set Theory. I wanted to examine how students figure out the different meanings of words in the natural and formal language. To do so, I analyzed six experiments. I compared three experiments with the experiments of my previous study in Iran. My research questions suggested using a qualitative research method. My theoretical framework built around theories of semiotic activities, which were used in the analysis. The results indicated that students can make unfortunate use of Euler–Venn diagrams. A set of sets was a difficult concept for students. Some words in natural language, even the word "set" in both natural and formal language, caused confusion for students when introduced in Set theoretic contexts. Students failed sometimes to distinguish between sets and elements. The experiments showed that students’ cultural context had affect on students' cognition regarding mathematical objects.
Inverse Free Electron Laser Interactions with Sub-Picosecond High Brightness Electron Beams

Advanced accelerators have great promise in reducing the size and cost of high energy colliders as well as bringing high brightness x-ray sources to the laboratory tabletop scale. The inverse free electron laser (IFEL) is a high gradient advanced accelerator scheme that is one of the most ecient ways of transferring energy from a laser to an electron beam. By copropagating a laser and a relativisticelectron beam through an undulator in vacuum and taking advantage of resonant ponderomotive motion of the electron beam, IFEL avoids the breakdown associated with other schemes that use a material to couple the laser fields to the electron beams.This dissertation provides an overview of IFEL, the photoinjector electron beams to be used in IFEL interactions, and two IFEL applications: compression and synchronization of a photoinjector electron beam to a laser application using THz driven IFEL and high gradient acceleration using IFEL.The numerically investigated THz IFEL application shows that with a 10 J THz 8 pulse train, an electron beam bunch length of 100 fs RMS can be compressed to 14 fs RMS and have the beam's time of arrival jitter relative to an external laser reduced by an order of magnitude.High gradient acceleration by IFEL was examined experimentally at Lawrence Livermore National Laboratory (LLNL). This experiment marks the first attempt to use sub-picosecond time pulse, TW peak power scale titanium:sapphire laser pulses to perform IFEL acceleration. The demonstrated energy gain from 77 to 120 MeV combined with particle tracking simulations shows an acceleratinggradient of over 200 MeV/m. Because the laser pulse length is the same order as the slippage experienced by the electron beam with respect to the laser and the time of arrival jitter has been measured to be greater than 2 ps, the overlap is investigated through relative single shot time of arrival measurements using electro-optic sampling based spatial encoding techniques. The temporal overlapmeasurement was found to be consistent with a cross-correlation model taking into account the independently measured laser and electron beam lengths.
Reversal of Multiple Drug Resistance in Cholangiocarcinoma by the Glutathione S -Transferase- (cid:1) -Specific Inhibitor O 1 -Hexadecyl- (cid:2) -glutamyl- S -benzylcysteinyl- D -phenylglycine Ethylester

Cholangiocarcinoma is markedly resistant to chemotherapy and has a dismal prognosis, but its mechanism of drug resistance is unknown. This study examines whether glutathione S -transferase- (cid:1) (GSTP1-1) is involved in resistance to anticancer drugs in cholangiocarcinoma and whether GSTP1-1-spe- cific inhibitors can overcome this resistance. First, immunohistochemical examination disclosed strong staining of all our 17 cholangiocarcinoma specimens for GSTP1-1, irrespective of histological type. Transfection of the GSTP1-1 antisense ex- pression vector into a human cholangiocarcinoma cell line (HuCCT1) apparently decreased its intracellular GSTP1-1 con- centration, and the sensitivity of transfectants to adriamycin (ADR), cisplatin, and alkylating agents such as melphalan and 4-hydroxyperoxycyclophosphamide (4-HC) was increased significantly, compared with that of mock transfectants. We next synthesized GSTP1-1-specific inhibitors by elongating the carbon chain of the ethylester at the N -terminal of (cid:2) -glutamyl- S -benzylcysteinyl-phenylglycyl diethylester and performed a pharmacokinetic study on them. Of six GSTP1-1 inhibitors tested, O 1 -hexadecyl- (cid:2) -glutamyl- S -benzylcysteinyl- D -phenylg-lycine ethylester (C16C2) showed the smallest volume of cen- tral compartment and smallest volume of distribution at steady state and the second smallest clearance, being the most effec- tive inhibitor in vivo. The IC 50 value of ADR or 4-HC for HuCCT1 cells decreased greater by treatment with C16C2 in a dose- dependent manner, paralleling the decrease in GSTP1-1 activity, than that of ADR or 4-HC alone. The antitumor activity of ADR or cyclophosphamide was clearly enhanced by combination therapy with C16C2 in a xenograft model. In conclusion, our results demonstrated that GSTP1-1 is a resistance factor for anticancer drugs in cholangiocarcinoma and that C16C2, a GSTP1-1-specific inhibitor, is a potent agent against the resistance. ,
Identification of Cancer Drivers using Classification of large DNA Methylation Dataset

- A well-studied genetic modification is crucial to regulate the functioning of the genome, which is done with the help of DNA Methylation. Alteration of DNA plays a vital role in tumor generation (tumorigenesis) and tumor-suppression. Therefore, studying DNA methylation data may help in identifying basic molecules or elements in body that indicates the presence of cancer. DNA methylation related data available from the public is huge – and considering the high number of methylated sites (features) present in the genome – it is crucial to have a technology for efficient processing of huge datasets. With the help of big data technologies, we propose an algorithm that can apply supervised learning in the form of classification methods to datasets with large amount of features. Through iterative deletion of selected features, extraction of equivalent classification models is possible using this algorithm. The experiments will be executed on DNA methylation datasets extracted from The Cancer Genome Atlas, where we will be focusing on three types of tumors: breast, kidney, and thyroid carcinomas. Several methylated sites and their associated genes will be extracted and classification will be performed on them with accurate performance. Thereafter, we will study the performance of our algorithm and compare it with other classifiers and with existing approaches used to analyze this data i.e, a wide-spread DNA methylation analysis method based on network analysis. Finally, we will be able to efficiently compute multiple alternative classification models and extract a set of candidate genes from DNA-methylation large datasets to be further examined to determine their role in cancer.
Reasoning and Argumentative Complexity*

The main objective of this paper is to propose a model of complexity, texture or argumentative density from the theoretical framework of text linguistics. To this effect, I have explored both the ability underlying the activity of speaking (the ἐνέργεια ) as the product of this competence (the ἔργον ). From the first perspective, some cognitive operations involved in this knowledge during the activity of discursive production are suggested which, as has been proposed, are projected onto the discourse in the form of more or less discourse complexity, texture or density. From the second, a normative model of the level of complexity of the product is proposed on the basis of the relational texture of the propositions and on the notion resulting of argumentative coherence.
Inﬂuence of Estrogen Modulation on Glia Activation in a Murine Model of Parkinson’s Disease

Epidemiological data suggest a sexual dimorphism in Parkinson disease (PD), with women showing lower risk of developing PD. Vulnerability of the nigrostriatal pathway may be inﬂuenced by exposure to estrogenic stimulation throughout fertile life. To further address this issue, we analyzed the progression of nigrostriatal damage, microglia and astrocyte activation and microglia polarization triggered by intrastriatal injection of dopaminergic neurotoxin 6-hydroxydopamine (6-OHDA) in male, female and ovariectomized (OVX) mice, as well as in OVX mice supplemented with 17 β estradiol (OVX + E). Animals were sacriﬁced at different time points following 6-OHDA injection and brain sections containing striatum and substantia nigra pars compacta (SNc) underwent immunohistochemistry for tyrosine hydroxylase (TH) (dopaminergic marker), immunoﬂuorescence for IBA1 and GFAP (markers of microglia and astrocyte activation, respectively) and triple immunoﬂorescent to identify polarization of microglia toward the cytotoxic M1 (DAPI/IBA1/TNF α ) or cytoprotective M2 (DAPI/IBA1/CD206) phenotype. SNc damage induced by 6-OHDA was signiﬁcantly higher in OVX mice, as compared to all other experimental groups, at 7 and 14 days after surgery. Astrocyte activation was higher in OVX mice with respect the other experimental groups, at all time points. Microglial activation in the SNc was detected at earlier time points in male, female and OVX + E, while in OVX mice was detected at all time-points. Microglia polarization toward the M2, but not the M1, phenotype was detected in female and OVX + E mice, while the M1 phenotype was observed only in male and OVX mice. Our results support the protective effects of estrogens against nigrostriatal degeneration, suggesting that such effects may be mediated by an interaction with microglia, which tend to polarize preferentially toward an M2, cytoprotective phenotype in the presence of intense estrogenic stimulation.
Effect of Ambient Gas Pressure on the Thermal Exfoliation of Graphite Oxide: Tuning the Number of Graphene Sheets

We have investigated the effect of ambient gas pressure (Argon) used during thermal exfoliation of graphite oxide on the number of graphene sheets in the resulting graphene. The ambience gas Ar pressures used are 80, 25, 1 atmosphere and 10-3 as well as 10-5 torr. We have found curious result that the number of graphene sheets in exfoliated graphene stack is dependent on the applied pressure for exfoliation of graphite oxide (GO). By lowering the exfoliation pressure, the numbers of sheets get reduced. The numbers of sheets in exfoliated graphene stack have been determined by Lorentzian fit of their respective 002 peak of XRD profile. The numbers of sheets have also been confirmed with high resolution transmission electron microscopy (HRTEM). The numbers of sheets in exfoliated graphene stack samples have been found to be 28, 12, 8, 5 and 3 at 80 atm, 25 atm, 1 atm, 10-3 torr and 10-5 torr pressures respectively. The results of present investigation suggest a simple but effective method for synthesizing graphene with a specific number of sheets.