Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and Analysis of HetNets with mm-Wave Multi-RAT Small Cells Deployed along Roads

We characterize a multi tier network with classical macro cells, and multi radio access technology (RAT) small cells, which are able to operate in microwave and millimeter-wave (mm-wave) bands. The small cells are assumed to be deployed along roads modeled as a Poisson line process. This characterization is more realistic as compared to the classical Poisson point processes typically used in literature. In this context, we derive the association and RAT selection probabilities of the typical user under various system parameters such as the small cell deployment density and mm-wave antenna gain, and with varying street densities. Finally, we calculate the signal to interference plus noise ratio (SINR) coverage probability for the typical user considering a tractable dominant interference based model for mm-wave interference. Our analysis reveals the need of deploying more small cells per street in cities with more streets to maintain coverage, and highlights that mm-wave RAT in small cells can help to improve the SINR performance of the users.
Ovarian Response and Cumulative Live Birth Rate of Women Undergoing In-Vitro Fertilisation Who Had Discordant Anti-Mullerian Hormone and Antral Follicle Count Measurements: A Retrospective Study

Objective To evaluate ovarian response and cumulative live birth rate of women undergoing in-vitro fertilization (IVF) treatment who had discordant baseline serum anti-Mullerian hormone (AMH) level and antral follicle count (AFC). Methods This is a retrospective cohort study on 1,046 women undergoing the first IVF cycle in Queen Mary Hospital, Hong Kong. Subjects receiving standard IVF treatment with the GnRH agonist long protocol were classified according to their quartiles of baseline AMH and AFC measurements after GnRH agonist down-regulation and before commencing ovarian stimulation. The number of retrieved oocytes, ovarian sensitivity index (OSI) and cumulative live-birth rate for each classification category were compared. Results Among our studied subjects, 32.2% were discordant in their AMH and AFC quartiles. Among them, those having higher AMH within the same AFC quartile had higher number of retrieved oocytes and cumulative live-birth rate. Subjects discordant in AMH and AFC had intermediate OSI which differed significantly compared to those concordant in AMH and AFC on either end. OSI of those discordant in AMH and AFC did not differ significantly whether either AMH or AFC quartile was higher than the other. Conclusions When AMH and AFC are discordant, the ovarian responsiveness is intermediate between that when both are concordant on either end. Women having higher AMH within the same AFC quartile had higher number of retrieved oocytes and cumulative live-birth rate.
Feature Structures Based Tree Adjoining Grammars

We have embedded Tree Adjoining Grammars (TAG) in a feature structure based unification system. The resulting system, Feature Structure based Tree Adjoining Grammars (FTAG), captures the principle of factoring dependencies and recursion, fundamental to TAG's. We show that FTAG has an enhanced descriptive capacity compared to TAG formalism. We consider some restricted versions of this system and some possible linguistic stipulations that can be made. We briefly describe a calculus to represent the structures used by this system, extending on the work of Rounds, and Kasper [Rounds et al. 1986, Kasper et al. 1986] involving the logical formulation of feature structures.
Noise reduction and enhancement of contour for median nerve detection in ultrasonic image

Three-dimensional nerve information is required for the diagnosis of peripheral neuropathy. We have developed a prototype manipulating device and developed an algorithm for extracting peripheral nerves from the ultrasonic wave images captured using this probe and produce three-dimensional median nerve. Unlike the images captured by artificially manipulating the probe, the images captured by our device captures images of same area only at once. They are partially clear making it easy to extract nerve contours, or partially unclear (blurry) which are difficult to extract. In order to solve this problem, this paper reports that noise reduction and inter-organization edge emphasis are applied to ultrasonic wave images and nerves are extracted using the images.
A novel technique for mosaicing of medical images

Image mosaicing has numerous applications in the area of computer vision, virtual reality, robotics, medical imaging, computer graphics and advertising. The creation of the seamless image mosaic often becomes a difficult task due to the presence of alignment errors and intensity discrepancies. The present paper discusses the development and implementation of a novel algorithm based on the discrete cosine transform (DCT) for mosaicing of medical images. The proposed method is implemented in three steps: image alignment, image reprojection, and image blending. In the first step, the geometric correspondence between the images to be mosaiced is calculated. The aim of the second step is to project the aligned images in a common compositing surface. Finally, the third step minimizes the intensity variations in the overlapping region of the final mosaic. As a result, a high quality seamless image mosaic is generated. The obtained results and its comparative analyses clearly illustrate the efficacy of the approach in obtaining visually pleasant mosaiced images.
The cost effectiveness of pharmacological smoking cessation therapies in developing countries: a case study in the Seychelles

Objective: To examine the incremental cost effectiveness of the five first line pharmacological smoking cessation therapies in the Seychelles and other developing countries. Design: A Markov chain cohort simulation. Subjects: Two simulated cohorts of smokers: (1) a reference cohort given physician counselling only; (2) a treatment cohort given counselling plus cessation therapy. Intervention: Addition of each of the five pharmacological cessation therapies to physician provided smoking cessation counselling. Main outcome measures: Cost per life-year saved (LYS) associated with the five pharmacotherapies. Effectiveness expressed as odds ratios for quitting associated with pharmacotherapies. Costs based on the additional physician time required and retail prices of the medications. Results: Based on prices for currently available generic medications on the global market, the incremental cost per LYS for a 45 year old in the Seychelles was US$599 for gum and $227 for bupropion. Assuming US treatment prices as a conservative estimate, the incremental cost per LYS was significantly higher, though still favourable in comparison to other common medical interventions: $3712 for nicotine gum, $1982 for nicotine patch, $4597 for nicotine spray, $4291 for nicotine inhaler, and $1324 for bupropion. Cost per LYS increased significantly upon application of higher discount rates, which may be used to reflect relatively high opportunity costs for health expenditures in developing countries with highly constrained resources and high overall mortality. Conclusion: Pharmacological cessation therapy can be highly cost effective as compared to other common medical interventions in low mortality, middle income countries, particularly if medications can be procured at low prices.
The Influence Of Parent-Child Conflict And Stressful Experiences On The Health Of Youth With Asthma

THE INFLUENCE OF PARENT-CHILD CONFLICT AND STRESSFUL EXPERIENCES ON THE HEALTH OF YOUTH WITH ASTHMA by ERIN THERESE TOBIN May 2013 Advisor: Dr. Richard Slatcher Major: Psychology (Clinical) Degree: Master of Arts Attaining a clear picture of everyday family interactions is essential for understanding how family stress and conflict adversely affects children’s health, especially in the context of chronic illness. Using a naturalistic observation sampling method called the Electronically Activated Recorder (EAR), we sought to investigate the effects of daily interpersonal conflicts and parental stress on pediatric asthma outcomes. We collected data from 81 children, aged 10 to 17 (M age = 12.88), and their primary caregiver as part of a larger study. Each child completed a pulmonary function test and self-report questionnaires of asthma symptoms. Asthma-related medical information was abstracted from their medical records. The Adult and Parent UCLA Life Stress Interview (LSI) assessed acute stress as the number of acutely stressful events in the past 6 months. Of these 81 participants, 45 children wore the EAR for 4 days. Trained research assistants coded the EAR files using the Everyday Child Home Observations (ECHO) Coding System for instances of interpersonal conflict (e.g., arguing, fighting, yelling) and asthma symptoms (e.g., coughing, wheezing). EAR-observed parent-child conflict (r = . 36, p EAR-observed family environment conflict (r = . 32, p youth reported asthma symptoms. Further, EAR-observed wheezing coded was positively
Probabilistic Hybrid Action Models for Predicting Concurrent Percept-Driven Robot Behavior

This paper develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans. PHAMs represent aspects of robot behavior that cannot be represented by most action models used in AI planning: the temporal structure of continuous control processes, their non-deterministic effects, and several modes of their interferences. The main contributions of the paper are: (1) PHAMs, a model of concurrent percept-driven behavior, its formalization, and proofs that the model generates probably, qualitatively accurate predictions; and (2) a resource-efficient inference method for PHAMs based on sampling projections from probabilistic action models and state descriptions. We discuss how PHAMs can be applied to planning the course of action of an autonomous robot office courier based on analytical and experimental results.
Deep-Belief-Network based Rescoring for Handwritten Word Recognition

This paper presents a novel verification approach towards improvement of handwriting recognition systems using a word hypotheses rescoring scheme by Deep Belief Networks (DBNs). A recurrent neural network based sequential text recognition system is used at first to provide the N-best recognition hypotheses of word images. Word hypotheses are aligned with the word image to obtain the character boundaries. Then, a verification approach using a DBN classifier is performed for each character segments. DBNs are recently proved to be very effective for a variety of machine learning problems. The character probabilities obtained from DBNs are next combined with the base recognition system. Finally, the N-best recognition hypotheses list is reranked according to the new score. We have compared our proposed approach with an MLP based rescoring approach on the Rimes dataset. The results obtained show that the verification approach using DBNs outperforms that of MLP systems.
Explorer Recent progress in translational research on neurovascular and neurodegenerative disorders

The already established and widely used intravenous application of recombinant tissue plasminogen activator as a re-opening strategy for acute vessel occlusion in ischemic stroke was recently added by mechanical thrombectomy, representing a fundamental progress in evidence-based medicine to improve the patient’s outcome. This has been paralleled by a swift increase in our understanding of pathomechanisms underlying many neurovascular diseases and most prevalent forms of dementia. Taken together, these current advances offer the potential to overcome almost two decades of marginally successful translational research on stroke and dementia, thereby spurring the entire field of translational neuroscience. Moreover, they may also pave the way for the renaissance of classical neuroprotective paradigms. This review reports and summarizes some of the most interesting and promising recent achievements in neurovascular and dementia research. It highlights sessions from the 9th International Symposium on Neuroprotection and Neurorepair that have been discussed from April 19th to 22nd in Leipzig, Germany. To acknowledge the emerging culture of interdisciplinary collaboration and research, special emphasis is given on translational stories ranging from fundamental research on neurodeand -regeneration to late stage translational or early stage clinical investigations.
Les réseaux de la conquête : rôle des filières bovines dans la structuration de l'espace sur les fronts pionniers d'Amazonie orientale brésilienne

La croissance du cheptel bovin et l'avancee des fronts pionniers sont deux processus mal connus en Amazonie bresilienne. Comment les filieres bovines determinent-elles la structuration spatiale des fronts pionniers d'Amazonie orientale ? Ce questionnement a d'abord conduit l'auteur a developper une analyse fonctionelle de la filiere bovine. L'approche systemique permet de dechiffrer la complexite des relations entre acteurs, et d'analyser l'influence de chaque sous-filiere sur les strategies individuelles et collectives. Puis l'auteur propose une conceptualisation de la notion de front pionnier, pour analyser comment les sous-filieres s'inscrivent dans ce systeme spatial en construction, et comment elles en determinent l'evolution. Il obtient deux types de resultats : la comprehension des principaux mecanismes d'interaction entre filiere bovine et territoires des pionniers, trois outils complementaires pour controler le developpement territorial des fronts pionniers.
Granulocyte Chemotaxis Measured in a Boyden Chamber Assay by Quantification of Neutrophil Elastase

The human polymorphonuclear leukocyte reaction in response to chemotactic or chemokinetic stimulation is often assayed using the Boyden chamber technique. We present a quick and reliable method for evaluating Boyden chamber experiments, which avoids time-consuming cell counting and does not require expensive equipment. This method is based on assaying human neutrophil elastase, a serine protease derived from polymorphonuclear leukocytes. We tested the method in different types of Boyden chambers equipped with two superimposed filters or a filter amnion membrane combination. The chambers were incubated with the cells for 2 h then dismantled and the elastase activity in supernatant, filters or membrane was assayed. The results were compared with the results obtained by cell counting, or measured by determination of myeloperoxidase. There was a good correlation between the cell count and elastase technique (r = 0.90), but the elastase method achieved higher intra- and interassay precision. Myeloperoxidase and elastase results also correlated well (r = 0.94) and showed comparable intra- and inter-assay precision. With the elastase method it was also possible to quantify polymorphonuclear leukocyte reactions on an amnion membrane surface. In amnion membrane assays the percentage of cells which reacted in response to formyl-peptide stimulation was not altered by varied cell concentrations, and polymorphonuclear leukocytes showed little unstimulated adherence or migration.
International Conference on Parallel Processing Closed Form Solutions for Bus and Tree Networks of Processors Load Sharing A Divisible Job

Optimal load allocation for load sharing a divisi¬ ble job over processors interconnected in either a bus or a tree network is considered. The processors are either equipped with front-end processors or not so equipped. Closed form solutions for the minimum fin¬ ish time and the optimal data allocation for each pro¬ cessor are obtained. The performance of large sym¬ metric tree networks is examined by aggregating the component links and processors into a single equiv¬ alent processor. This allows an easy examination of large tree networks. In addition it becomes possible to find a closed form solution for the optimal amount of data that is to be assigned to each processor in the tree network in order to achieve the minimum finish time.
Synthetic B-Cell Epitopes Eliciting Cross-Neutralizing Antibodies: Strategies for Future Dengue Vaccine

Dengue virus (DENV) is a major public health threat worldwide. A key element in protection from dengue fever is the neutralising antibody response. Anti-dengue IgG purified from DENV-2 infected human sera showed reactivity against several peptides when evaluated by ELISA and epitope extraction techniques. A multi-step computational approach predicted six antigenic regions within the E protein of DENV-2 that concur with the 6 epitopes identified by the combined ELISA and epitope extraction approach. The selected peptides representing B-cell epitopes were attached to a known dengue T-helper epitope and evaluated for their vaccine potency. Immunization of mice revealed two novel synthetic vaccine constructs that elicited good humoral immune responses and produced cross-reactive neutralising antibodies against DENV-1, 2 and 3. The findings indicate new directions for epitope mapping and contribute towards the future development of multi-epitope based synthetic peptide vaccine.
A HfO2 based 800V/300°C Au-free AlGaN/GaN-on-Si HEMT technology

Innovative 800V/300°C AlGaN/GaN-on-Si high electron mobility transistors (HEMTs) fabricated with a 4-inch Si CMOS compatible technology are presented in this paper. High performance AlGaN/GaN MIS gated HEMT (MIS-HEMT) and passivated HEMT (i-HEMT) were fabricated using 5nm-thick HfO<sub>2</sub>, and 30nm-thick CVD Si<sub>3</sub>N<sub>4</sub> as the gate and passivation insulator, respectively. Contact resistance maps yield reduced R<sub>c</sub> of 1.32±0.26 Ωmm for Au-free compared to 0.86±0.58 Ωmm for conventional Au-based Ohmic metallization. The off-state breakdown voltage is around 800V with a specific on-resistance of 2 mΩcm<sup>2</sup>. Gate and drain leakage currents as well as dynamic I-V trapping are significantly improved with the MIS-HEMT architecture with almost no trade-off to the on-state.
Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval

Given a query photo issued by a user (q-user), the landmark retrieval is to return a set of photos with their landmarks similar to those of the query, while the existing studies on the landmark retrieval focus on exploiting geometries of landmarks for similarity matches between candidate photos and a query photo. We observe that the same landmarks provided by different users over social media community may convey different geometry information depending on the viewpoints and/or angles, and may, subsequently, yield very different results. In fact, dealing with the landmarks with low quality shapes caused by the photography of q-users is often nontrivial and has seldom been studied. In this paper, we propose a novel framework, namely, multi-query expansions, to retrieve semantically robust landmarks by two steps. First, we identify the top- $k$ photos regarding the latent topics of a query landmark to construct multi-query set so as to remedy its possible low quality shape. For this purpose, we significantly extend the techniques of Latent Dirichlet Allocation. Then, motivated by the typical collaborative filtering methods, we propose to learn a collaborative deep networks-based semantically, nonlinear, and high-level features over the latent factor for landmark photo as the training set, which is formed by matrix factorization over collaborative user-photo matrix regarding the multi-query set. The learned deep network is further applied to generate the features for all the other photos, meanwhile resulting into a compact multi-query set within such space. Then, the final ranking scores are calculated over the high-level feature space between the multi-query set and all other photos, which are ranked to serve as the final ranking list of landmark retrieval. Extensive experiments are conducted on real-world social media data with both landmark photos together with their user information to show the superior performance over the existing methods, especially our recently proposed multi-query based mid-level pattern representation method [1].
The effectiveness of Grade One English interactive radio instruction programs in Ethiopia

The aim of this study was to find out whether Interactive Radio Instruction (IRI) English Programs in Grade One were effective in Ethiopia. The primary objective of the study was to measure student learning gains in English Listening Comprehension. A secondary objective was to determine if IRI programs had differential impact on girls and boys, and on urban/rural schools. A basic experimental design was used to compare the learning gains of children in classes using the IRI English programs and children in traditional English classes. Participants in this study constituted control and experimental groups and they were randomly selected and assigned to their respective groups. The sample size was 1466 children for both groups. The dependent variable, student scholastic achievement score was measured at two occasions: pre-test and post-test. For the pre-test both control and experimental students were given a listening comprehension test, which was recorded on a cassette. After an interval of seven months, which constituted a treatment period, the same test was given to the same students in their respective groups. The treatment consisted of 5 fifteen minute interactive radio lessons every week in experimental schools. Traditional instruction was given in the control schools and there was no exposure of the students to IRI in these schools. Results indicate that students exposed to IRI gained significantly more than students in non-IRI or traditional instruction. In addition, in the IRI classes, female students gained more than male students. From this it was recommended that the use of interactive radio programs has to be expanded to benefit all students in Ethiopian primary schools.
A CROC stronger than ROC: measuring, visualizing and optimizing early retrieval

MOTIVATION The performance of classifiers is often assessed using Receiver Operating Characteristic ROC [or (AC) accumulation curve or enrichment curve] curves and the corresponding areas under the curves (AUCs). However, in many fundamental problems ranging from information retrieval to drug discovery, only the very top of the ranked list of predictions is of any interest and ROCs and AUCs are not very useful. New metrics, visualizations and optimization tools are needed to address this 'early retrieval' problem. RESULTS To address the early retrieval problem, we develop the general concentrated ROC (CROC) framework. In this framework, any relevant portion of the ROC (or AC) curve is magnified smoothly by an appropriate continuous transformation of the coordinates with a corresponding magnification factor. Appropriate families of magnification functions confined to the unit square are derived and their properties are analyzed together with the resulting CROC curves. The area under the CROC curve (AUC[CROC]) can be used to assess early retrieval. The general framework is demonstrated on a drug discovery problem and used to discriminate more accurately the early retrieval performance of five different predictors. From this framework, we propose a novel metric and visualization-the CROC(exp), an exponential transform of the ROC curve-as an alternative to other methods. The CROC(exp) provides a principled, flexible and effective way for measuring and visualizing early retrieval performance with excellent statistical power. Corresponding methods for optimizing early retrieval are also described in the Appendix. AVAILABILITY Datasets are publicly available. Python code and command-line utilities implementing CROC curves and metrics are available at http://pypi.python. org/pypi/CROC/ CONTACT: pfbaldi@ics.uci. edu