LLukas22/scidocs huggingface dataset:
Managing congenitally missing lateral incisors. Part I: Canine substitution.

UNLABELLED
Dentists often encounter patients with missing or malformed teeth. The maxillary lateral incisor is the second most common congenitally absent tooth. There are three treatment options that exist for replacing missing lateral incisors. They include canine substitution, a tooth-supported restoration, or a single-tooth implant. Selecting the appropriate option depends on the malocclusion, specific space requirements, tooth-size relationship, and size and shape of the canine. The ideal treatment is the most conservative option that satisfies individual esthetic and functional requirements. Often the ideal option is canine substitution. Although the orthodontist positions the canine in the most esthetic and functional location, the restorative dentist often needs to place a porcelain veneer or crown to re-create normal lateral incisor shape and color. This article closely examines patient selection and illustrates the importance of interdisciplinary treatment planning to achieve optimal esthetics. It is the first in a three-part series discussing the three treatment alternatives for replacing missing lateral incisors.


CLINICAL SIGNIFICANCE
Patients with congenitally missing lateral incisors often raise difficult treatment planning issues. Therefore, to produce the most predictable esthetic results, it is important to choose the treatment that will best address the initial diagnosis. This article is the first in a three-part series that describes the different treatments available for patients with congenitally missing lateral incisors. This first article focuses on canine substitution as a method of tooth replacement for these missing teeth. The general dentist will learn to evaluate specific patient selection criteria and determine whether canine substitution is an appropriate treatment alternative for replacing missing lateral incisors. The orthodontist will understand how to position the canines to satisfy functional requirements and achieve proper esthetics. Finally, the importance of interdisciplinary team treatment planning is emphasized as a requirement for achieving optimal final esthetics.
A Hierarchical Genetic Optimization of a Fuzzy Logic System for Flow Control in Micro Grids

Bio-inspired algorithms like Genetic Algorithms and Fuzzy Inference Systems (FIS) are nowadays widely adopted as hybrid techniques in commercial and industrial environment. In this paper we present an interesting application of the fuzzy-GA paradigm to Smart Grids. The main aim consists in performing decision making for power flow management tasks in the proposed microgrid model equipped by renewable sources and an energy storage system, taking into account the economical profit in energy trading with the main-grid. In particular this study focuses on the application of a Hierarchical Genetic Algorithm (HGA) for tuning the Rule Base (RB) of a Fuzzy Inference System (FIS), trying to discover a minimal fuzzy rules set in a Fuzzy Logic Controller (FLC) adopted to perform decision making in the microgrid. The HGA rationale focuses on a particular encoding scheme, based on control genes and parametric genes applied to the optimization of the FIS parameters, allowing to perform a reduction in the structural complexity of the RB. This approach will be referred in the following as fuzzy-HGA. Results are compared with a simpler approach based on a classic fuzzy-GA scheme, where both FIS parameters and rule weights are tuned, while the number of fuzzy rules is fixed in advance. Experiments shows how the fuzzy-HGA approach adopted for the synthesis of the proposed controller outperforms the classic fuzzy-GA scheme, increasing the accounting profit by 67% in the considered energy trading problem yielding at the same time a simpler RB. keywords: Microgrid, Energy Management System, Battery Energy Storage, Power Flow Optimization, Storage System Management, Fuzzy Systems, Evolutionary Computation, Hierarchical Genetic Algorithms.
Backache: a rare diagnosis and unusual complication

We report an adolescent girl who presented with an acute exacerbation of a chronic backache of 6 months duration. She complained of dribbling micturition, constipation, and an irresistible urge to strain for 72 h. In the waiting area of the local hospital she developed sudden, severe chest pain with progressive swelling of the upper torso. This proved to be the mode of presentation of a haematocolpos due to an imperforate hymen with the unusual complication of mediastinal emphysema. Imperforate hymen is a rare diagnosis, but should be considered when dealing with an adolescent girl with lower abdominal symptoms or backache.
A Novel Position Sensorless Control of a Four-Switch, Brushless DC Motor Drive Without Phase Shifter

This paper presents the analysis, design, and implementation of a cost-effective sensorless control technique for a low-cost four-switch, three-phase inverter brushless dc motor drive. The proposed sensorless technique is based on the detection of zero crossing points (ZCPs) of three voltage functions that are derived from the filtered terminal voltages nuao and nubo. Six commutation instants are provided that coincide to ZCPs of voltage functions. Hence, there is no need for any 30deg or 90deg phase delay that is prevalent in conventional sensorless methods. Two low-pass filters are used for elimination of high-frequency noises and calculation of average terminal voltages. Also, a direct phase current control method is used to control the phase currents in the four-switch inverter. An analytical study on position estimation error is discussed, and a correction method for some typical applications is suggested. The performance of the developed sensorless technique is demonstrated by simulation, and then, it is implemented using TMS320LF2407A DSP. Experimental results are provided to confirm the simulations.
Experiences of pregnancy and motherhood among teenage mothers in a suburb of Accra, Ghana: a qualitative study

BACKGROUND
The proportion of teenage girls who are mothers or who are currently pregnant in sub-Saharan African countries is staggering. There are many studies regarding teenage pregnancy, unsafe abortions, and family planning among teenagers, but very little is known about what happens after pregnancy, ie, the experience of teenage motherhood. Several studies in Ghana have identified the determinants of early sexual activity, contraception, and unsafe abortion, with teenage motherhood only mentioned in passing. Few studies have explored the experiences of adolescent mothers in detail with regard to their pregnancy and childbirth. This qualitative study explores the experiences of adolescent mothers during pregnancy, childbirth, and care of their newborns.


METHODS
This qualitative study was based on data from focus group discussions and indepth interviews with teenage mothers in a suburb in Accra. Participants were recruited from health facilities as well as by snowball sampling.


RESULTS
Some of the participants became pregnant as a result of transactional sex in order to meet their basic needs, while others became pregnant as a result of sexual violence and exploitation. A few others wanted to become pregnant to command respect from people in society. In nearly all cases, parents and guardians of the adolescent mothers were upset in the initial stages when they heard the news of the pregnancy. One key finding, quite different from in other societies, was how often teenage pregnancies are eventually accepted, by both the young women and their families. Also observed was a rarity of willingness to resort to induced abortion.


CONCLUSION
Special programs should be initiated by the government and the various responsible departments to address ignorance on sexual matters, and the challenges and risks associated with pregnancy and parenting by adolescents. Parenting techniques should be taught in sex education programs.
Internet of Things : Perspectives , Challenges and Opportunities

The Internet of things can be defined as to make the “things” belong to the Internet. However, many wonder if the current Internet can support such a challenge. For this and other reasons, hundreds of worldwide initiatives to redesign the Internet are underway. This article discusses the perspectives, challenges and opportunities behind a future Internet that fully supports the “things”, as well as how the “things” can help in the design of a more synergistic future Internet. Keywords–Internet of things, smart things, future Internet, software-defined networking, service-centrism, informationcentrism, ID/Loc splitting, security, privacy, trust.
MetaCluster 4.0: A Novel Binning Algorithm for NGS Reads and Huge Number of Species

Next-generation sequencing (NGS) technologies allow the sequencing of microbial communities directly from the environment without prior culturing. The output of environmental DNA sequencing consists of many reads from genomes of different unknown species, making the clustering together reads from the same (or similar) species (also known as binning) a crucial step. The difficulties of the binning problem are due to the following four factors: (1) the lack of reference genomes; (2) uneven abundance ratio of species; (3) short NGS reads; and (4) a large number of species (can be more than a hundred). None of the existing binning tools can handle all four factors. No tools, including both AbundanceBin and MetaCluster 3.0, have demonstrated reasonable performance on a sample with more than 20 species. In this article, we introduce MetaCluster 4.0, an unsupervised binning algorithm that can accurately (with about 80% precision and sensitivity in all cases and at least 90% in some cases) and efficiently bin short reads with varying abundance ratios and is able to handle datasets with 100 species. The novelty of MetaCluster 4.0 stems from solving a few important problems: how to divide reads into groups by a probabilistic approach, how to estimate the 4-mer distribution of each group, how to estimate the number of species, and how to modify MetaCluster 3.0 to handle a large number of species. We show that Meta Cluster 4.0 is effective for both simulated and real datasets. Supplementary Material is available at www.liebertonline.com/cmb.
Information Disclosure, Cognitive Biases and Payday Borrowing

If people face cognitive limitations or biases that lead to financial mistakes, what are possible ways lawmakers can help? One approach is to remove the option of the bad decision; another approach is to increase financial education such that individuals can reason through choices when they arise. A third, less discussed, approach is to mandate disclosure of information in a form that enables people to overcome limitations or biases at the point of the decision. This third approach is the topic of this paper. We study whether and what information can be disclosed to payday loan borrowers to lower their use of high-cost debt via a field experiment at a national chain of payday lenders. We find that information that helps people think less narrowly (over time) about the cost of payday borrowing, and in particular information that reinforces the adding-up effect over pay cycles of the dollar fees incurred on a payday loan, reduces the take-up of payday loans by about 10 percent in a 4 month-window following exposure to the new information. Overall, our results suggest that consumer information regulations based on a deeper understanding of cognitive biases might be an effective policy tool when it comes to regulating payday borrowing, and possibly other financial and non-financial products. Both authors are from the Booth School of Business, University of Chicago, 5807 S. Woodlawn Avenue, Chicago, IL 60637. Contact emails are marianne.bertrand@ChicagoBooth.edu and adair.morse@ChicagoBooth.edu. We thank the Initiative on Global Markets at the University of Chicago, the National Poverty Center at the University of Michigan, the Templeton Foundation, the William Ladany Memorial Faculty Research Fund, the Center for Research on Security Prices, and the Stigler Center for financial support. We also would like to thank a number of people for helpful comments, including Shawn Cole, Victoria Ivashina, AnnaMaria Lusardi, Tavneet Suri, Jeremy Tobacman, Peter Tufano and seminar or conference participants at Booth School of Business, the CEPR-Gerzensee Asset Pricing Week, Copenhagen Business School, the University of Illinois at Chicago, the European Finance Association Summer Meetings, the FDIC-JFSR Bank Research Conference, the Milton Freidman Conference on Finance and Development, the National Poverty Center Spring 2009 Conference, the NBER Summer Institute in Corporate Finance, the NBER Behavioral Finance Group, the Norwegian School of Management, the Philadelphia Federal Reserve Conference on Recent Developments in Consumer Credit and Payments, the Stockholm School of Economics and Wharton. 1
Learning to Probabilistically Identify Authoritative Documents

We describe a model of document citation that learns to identify hubs and authorities in a set of linked documents such as pages retrieved from the world wide web or papers retrieved from a research paper archive Un like the popular HITS algorithm which re lies on dubious statistical assumptions our model provides probabilistic estimates that have clear semantics We also nd that in general the identi ed authoritative docu ments correspond better to human intuition
Replication of Association of the PTPRC Gene With Response to Anti–Tumor Necrosis Factor Therapy in a Large UK Cohort

OBJECTIVE
Several rheumatoid arthritis (RA) susceptibility variants map close to genes involved in the tumor necrosis factor (TNF) signaling pathway, prompting the investigation of RA susceptibility variants in studies of predictors of response to TNF blockade. Based on a previously reported association of RA with the PTPRC genetic locus, the present study was undertaken to test established RA susceptibility variants, including PTPRC, in the prediction of response to TNF blockade in a large cohort of patients from the UK.


METHODS
DNA was extracted from the blood of 1,115 UK patients with RA who were receiving anti-TNF biologic therapy. Samples were analyzed for 29 single-nucleotide polymorphisms (SNPs) previously established as RA susceptibility variants. In the primary analysis, the effect of each SNP on treatment response was assessed by linear regression, using an additive model, in which absolute change in the Disease Activity Score in 28 joints at 6 months of followup was the outcome measure. In a secondary analysis, logistic regression models were used to compare patients with a good treatment response (n = 274) to those with a poor response (n = 195), as defined using the European League Against Rheumatism response criteria. Results were combined with those from previous studies to confirm the findings by meta-analysis.


RESULTS
The PTPRC rs10919563 SNP was associated with improved treatment response in both the primary analysis (regression coefficient 0.19, 95% confidence interval [95% CI] 0.09, 0.37; P = 0.04) and secondary analysis (odds ratio 0.62, 95% CI 0.40, 0.95; P = 0.03). A meta-analysis combining these data with the results from a previous study strengthened the evidence for association with the PTPRC SNP (P = 5.13 × 10(-5) ). No convincing association of the treatment response with other candidate loci was detected.


CONCLUSION
Presence of the rs10919563 RA susceptibility variant at the PTPRC gene locus predicts improved response to anti-TNF biologic therapy. Fine-mapping studies are required to determine whether this SNP or another variant at the locus provides the greatest predictive accuracy for treatment response.
Diversified potentials of Ocimum sanctum Linn (Tulsi):An exhaustive survey

Ocimum sanctum (also tulsi, tulasī, or Holy Basil is an aromatic plant in the family Lamiaceae which is native throughout the old world tropics and widespread as a cultivated plant and an escaped weed. Tulsi is cultivated for religious and medicinal purposes, and for its essential oil. It is widely known across South Asia as a medicinal plant and an herbal tea, commonly used in Ayurveda, and has an important role within the Vaishnavite tradition of Hinduism, in which devotees perform worship involving tulsi plants or leaves. Eugenol (l-hydroxy-2-methoxy-4allylbenzene), the active constituent present in Ocimum sanctum L., has been found to be largely responsible for the therapeutic potentials of Tulsi. In the present review, efforts have been made to sum up different aspects of scientific studies on this medicinal plant. Scientific evidences are available on various medicinal aspects i.e. antimicrobial, adaptogenic, antidiabetic, hepatoprotective, anti-inflammatory, anti-carcinogenic, radioprotective, immunomodulatory, neuroprotective, cardio-protective, etc. Thus, Ocimum sanctum contain several bioactive compounds may contribute to the health effects and are easily available for consumption to increase the nutritional status as well as act as safe guarding against possible deficiencies.
A Cell-Based Systems Biology Assessment of Human Blood to Monitor Immune Responses after Influenza Vaccination

Systems biology is an approach to comprehensively study complex interactions within a biological system. Most published systems vaccinology studies have utilized whole blood or peripheral blood mononuclear cells (PBMC) to monitor the immune response after vaccination. Because human blood is comprised of multiple hematopoietic cell types, the potential for masking responses of under-represented cell populations is increased when analyzing whole blood or PBMC. To investigate the contribution of individual cell types to the immune response after vaccination, we established a rapid and efficient method to purify human T and B cells, natural killer (NK) cells, myeloid dendritic cells (mDC), monocytes, and neutrophils from fresh venous blood. Purified cells were fractionated and processed in a single day. RNA-Seq and quantitative shotgun proteomics were performed to determine expression profiles for each cell type prior to and after inactivated seasonal influenza vaccination. Our results show that transcriptomic and proteomic profiles generated from purified immune cells differ significantly from PBMC. Differential expression analysis for each immune cell type also shows unique transcriptomic and proteomic expression profiles as well as changing biological networks at early time points after vaccination. This cell type-specific information provides a more comprehensive approach to monitor vaccine responses.
Selective agonist of group II glutamate metabotropic receptors, LY354740, inhibits tolerance to analgesic effects of morphine in mice.

1. Antagonists of glutamate N-methyl-D-aspartate (NMDA) subtype receptor inhibit the development of tolerance to the antinociceptive effects of opioids. Another way to inhibit the function of glutamate receptors is the stimulation of presynaptic metabotropic group II (mGluRII) receptors. Because LY354740 ((+)-2-aminobicyclo [3,1,0] hexane-2,6-dicarboxylic acid) is the first systemically active agonist of group II mGlu receptors, we investigated if this compound might inhibit the development of tolerance to antinociceptive effects of morphine and fentanyl. 2. As assessed by cumulative dose-response approach in the tail-flick test, administration of 10 mg kg(-1) morphine bid s.c. to male Albino Swiss mice for 6 days, right-shifted morphine dose-response curve by approximately 4 fold. In a separate group of mice, 12 injections of 0.04 mg kg(-1) of fentanyl over 3 days, right-shifted fentanyl dose-response curve by approximately 3.3 fold. 3. In experiment 1, LY354740 (1 and 10, but not 0.1 mg kg(-1)) as well as the reference compound, an uncompetitive NMDA receptor antagonist memantine (7.5 mg kg(-1)) inhibited the development of morphine tolerance. Neither LY354740 (10 mg kg(-1)) nor memantine (7.5 mg kg(-1)) affected the development of tolerance to fentanyl. In experiment 2, neither LY354740 (1 and 10 mg kg(-1)) nor memantine (7.5 mg kg(-1)) affected the tail-flick antinociceptive response, or the acute antinociceptive effect of morphine. 4. The present results are the first to suggest that the development of antinociceptive morphine tolerance may be inhibited by metabotropic group II glutamate agonist.
Relationships Between Housing and Food Insecurity, Frequent Mental Distress, and Insufficient Sleep Among Adults in 12 US States, 2009

INTRODUCTION
Housing insecurity and food insecurity may be psychological stressors associated with insufficient sleep. Frequent mental distress may mediate the relationships between these variables. The objective of this study was to examine the relationships between housing insecurity and food insecurity, frequent mental distress, and insufficient sleep.


METHODS
We analyzed data from the 2009 Behavioral Risk Factor Surveillance System in 12 states. Housing insecurity and food insecurity were defined as being worried or stressed "sometimes," "usually," or "always" during the previous 12 months about having enough money to pay rent or mortgage or to buy nutritious meals.


RESULTS
Of 68,111 respondents, 26.4% reported frequent insufficient sleep, 28.5% reported housing insecurity, 19.3% reported food insecurity, and 10.8% reported frequent mental distress. The prevalence of frequent insufficient sleep was significantly greater among those who reported housing insecurity (37.7% vs 21.6%) or food insecurity (41.1% vs 22.9%) than among those who did not. The prevalence of frequent mental distress was also significantly greater among those reporting housing insecurity (20.1% vs 6.8%) and food insecurity (23.5% vs 7.7%) than those who did not. The association between housing insecurity or food insecurity and frequent insufficient sleep remained significant after adjustment for other sociodemographic variables and frequent mental distress.


CONCLUSION
Sleep health and mental health are embedded in the social context. Research is needed to assess whether interventions that reduce housing insecurity and food insecurity will also improve sleep health and mental health.
Facial Expression Recognition Based on NMF and SVM

A novel approach to facial expression recognition (FER) based on the combination of Non-negative Matrix Factorization (NMF) and Support Vector Machine (SVM) was proposed. One key step in FER is to extract expression features from the original face images. NMF is an effective approach to extract expression features because NMF decomposition makes the reconstruction of expression images in a non-subtractive way and is much similar to the process of forming unity from parts. The proposed algorithm first processes facial expression image with histogram equalization operator. Then NMF method is used for feature dimension reduction and SVM for classification. Finally, the algorithm was implemented with Matlab and experimented in Japanese female facial expression database (JAFEE database). A recognition rate of 66.19% was obtained and showed the effectiveness of the proposed algorithm