LLukas22/scidocs huggingface dataset:
Religion and Mental Health: The Case of American Muslims

Muslims have lived in America for centuries and their numbers are increasing like those of any other ethnic or religious group living in America. There is a growing awareness among mental health professionals of how to deal with mental health issues of the American minorities but little, if any, research is available on American Muslims. American living presents unique challenges to the Muslims who stick to their Islamic faith. The nature of Islamic faith and the concept of mental health in Islam are presented in this paper as well as the stressors that lead to mental health problems among the Muslims. The article also covers the response of Muslim communities to such challenges and the prescriptions given in Islam for positive mental health. Recommendations are outlined in the hope of initiating relevant research that would address the psychological needs of this largely neglected minority.
Relaxed Lasso

The Lasso is an attractive regularisation method for high-dimensional regression. It combines variable selection with an efficient computational procedure. However, the rate of convergence of the Lasso is slow for some sparse high-dimensional data, where the number of predictor variables is growing fast with the number of observations. Moreover, many noise variables are selected if the estimator is chosen by cross-validation. It is shown that the contradicting demands of an efficient computational procedure and fast convergence rates of the 2-loss can be overcome by a two-stage procedure, termed the relaxed Lasso. For orthogonal designs, the relaxed Lasso provides a continuum of solutions that include both softand hard-thresholding of estimators. The relaxed Lasso solutions include all regular Lasso solutions and computation of all relaxed Lasso solutions is often identically expensive as computing all regular Lasso solutions. Theoretical and numerical results demonstrate that the relaxed Lasso produces sparser models with equal or lower prediction loss than the regular Lasso estimator for high-dimensional data. © 2007 Elsevier B.V. All rights reserved.
Makescape: my diary of landscape

Late October 2004 Mid January 2005: As an architect engaged in postgraduate research in a department of geography where I am surrounded by physical geographers, historical geographers and cultural geographers, I have spent a large portion of the past few months submerged in various writings on the term 'landscape'. Covering as broad a scope as possible, my reading has led me into many fields of exploration. From art critics to academic geographers, from historians to landscape architects, it appears that each group has a different take on the meaning, position, and approach to landscape. The deeper and deeper I have gone into these areas, the more muddied my understandings have become. It feels as though my own once-clear understandings of what landscape is, or could be, are becoming lost in a mire amongst these competing meanings. Landscape: A cultural construction? A social process? A physical thing?
Automatic optimisation of parallel linear algebra routines in systems with variable load

The architecture of an automatically tuned linear algebra library proposed in previous works is extended in order to adapt itself to platforms where both the CPU load and the network traffic vary. During the installation process in a system, the linear algebra routines will be tuned automatically to the system conditions: hardware characteristics and basic libraries used in the linear algebra routines. At run-time the parameters that define the system characteristics are adjusted to the actual load of the platform. The design methodology is analysed with a block LU factorisation. Variants for sequential and parallel versions of this routine on a logical rectangular mesh of processors are considered. The behavior of the algorithm is studied with message-passing, using MPI on a cluster of PCs. The experiments show that the configurable parameters of the linear algebra routines can be adjusted during the run-time process despite the variability of the environment.
Aggressive behavior and reproductive physiology in females of the social cichlid fish Cichlasoma dimerus

The South American cichlid fish Cichlasoma dimerus is a freshwater species that presents social hierarchies, a highly organized breeding activity, biparental care and a high frequency of spawning. Spawning is followed by a period of parental care (about 20 days in aquaria conditions) during which the cooperative pair takes care of the eggs, both by fanning them and by removing dead ones. The different spawning events in the reproductive period were classified as female reproductive stages which can be subdivided in four phases, according to their offspring degree of development: (1) female with prespawning activity (day 0), (2) female with eggs (day 1 after fertilization), (3) female with hatched larvae (day 3 after fertilization) and (4) female with swimming larvae (FSL, day 8 after fertilization). In Perciform species gonadotropin-releasing hormone type-3 (GnRH3) neurons are associated with the olfactory bulbs acting as a potent neuromodulator of reproductive behaviors in males. The aim of this study is to characterize the GnRH3 neuronal system in females of C. dimerus in relation with aggressive behavior and reproductive physiology during different phases of the reproductive period. Females with prespawning activity were the most aggressive ones showing GnRH-3 neurons with bigger nuclear and somatic area and higher optical density than the others. They also presented the highest levels of plasma androgen and estradiol and maximum gonadosomatic indexes. These results provide information about the regulation and functioning of hypothalamus-pituitary-gonads axis during reproduction in a species with highly organized breeding activity.
Estimation and Forecast of Wind Power Generation by FTDNN and NARX-net based models for Energy Management Purpose in Smart Grids

This paper is focused on the prediction and forecast of climate time series, particularly useful for planning and management of the power grid, by artificial neural networks. An appropriate prediction and forecast of climate variables, indeed, improves the overall efficiency and performance of renewable power plants connected to the power grid. On such a basis, the application of suitable Artificial Neural Networks (ANNs) to the field of wind power generation is proposed. In particular, two dynamic recurrent ANNs, i.e., the Focused Time-Delay Neural Network (FTDNN) and the Nonlinear autoregressive network with exogenous inputs (NARX), are used to develop a model for the estimate and forecast of daily wind speed. Results, applied to a turbine model, allow the produced power to be calculated for energy management and planning purpose in smart grids.
Effects of acute systemic administration of cannabidiol on sleep-wake cycle in rats.

UNLABELLED
Cannabidiol (CBD) is one of the main components of Cannabis sativa and has a wide spectrum of action, including effects in the sleep-wake cycle.


OBJECTIVE
The objective of this paper is to assess the effects on sleep of acute systemic administration of CBD.


METHOD
Adult male Wistar rats were randomly distributed into four groups that received intraperitoneal injections of CBD 2.5 mg/kg, CBD 10 mg/kg, CBD 40 mg/kg or vehicle (n=seven animals/group). Sleep recordings were made during light and dark periods for four days: two days of baseline recording, one day of drug administration (test), and one day after drug (post-test).


RESULTS
During the light period of the test day, the total percentage of sleep significantly increased in the groups treated with 10 and 40 mg/kg of CBD compared to placebo. REM sleep latency increased in the group injected with CBD 40 mg/kg and was significantly decreased with the dose of 10 mg/kg on the post-test day. There was an increase in the time of SWS in the group treated with CBD 40 mg/kg, although this result did not reach statistical significance.


CONCLUSION
The systemic acute administration of CBD appears to increase total sleep time, in addition to increasing sleep latency in the light period of the day of administration.
Spatio-Temporally Consistent Correspondence for Dense Dynamic Scene Modeling

Local Rigidity Test Problem. Dense 3D reconstruction of a dynamic foreground subject from a pair of unsynchronized videos with unknown temporal overlap. Challenges: 1. How to identify temporal overlap in terms of estimated dynamic geometry . 2. How to robustly estimate geometry without knowledge of temporal overlap. Key Ideas: 1. Define the cardinality of the maximal set of locally rigid feature tracks as a measure of spatio-temporal consistency of a pair of video sub-sequences. 2. Develop a closed-loop track correspondence refinement process to find the maximal set of rigid tracks. Contributions: 1. We exploit the correlation between temporal alignment errors and geometric estimation errors. 2. We provide a joint solution to the geometry estimation and temporal the video alignment problems. 3. Model-free (i.e. data-driven) framework with wide applicability.
Biologic Approaches for the Treatment of Partial Tears of the Anterior Cruciate Ligament

BACKGROUND
Anterior cruciate ligament reconstruction (ACLR) has been established as the gold standard for treatment of complete ruptures of the anterior cruciate ligament (ACL) in active, symptomatic individuals. In contrast, treatment of partial tears of the ACL remains controversial. Biologically augmented ACL-repair techniques are expanding in an attempt to regenerate and improve healing and outcomes of both the native ACL and the reconstructed graft tissue.


PURPOSE
To review the biologic treatment options for partial tears of the ACL.


STUDY DESIGN
Review.


METHODS
A literature review was performed that included searches of PubMed, Medline, and Cochrane databases using the following keywords: partial tear of the ACL, ACL repair, bone marrow concentrate, growth factors/healing enhancement, platelet-rich plasma (PRP), stem cell therapy.


RESULTS
The use of novel biologic ACL repair techniques, including growth factors, PRP, stem cells, and bioscaffolds, have been reported to result in promising preclinical and short-term clinical outcomes.


CONCLUSION
The potential benefits of these biological augmentation approaches for partial ACL tears are improved healing, better proprioception, and a faster return to sport and activities of daily living when compared with standard reconstruction procedures. However, long-term studies with larger cohorts of patients and with technique validation are necessary to assess the real effect of these approaches.
MediConceptNet: An Affinity Score Based Medical Concept Network

In healthcare, information extraction is essential in building automatic domain-specific applications. Medical concepts and their semantic identification take an important role to develop a network for visualizing medical concepts and their relations. The challenge appears while available medical corpora are only in either unstructured or semi-structured forms. In the present paper, to overcome the challenge and consequently to construct a structured corpus, we apply a domain-specific lexicon, namely WordNet of Medical Event. Medical concepts assigned by this lexicon and their affinity score, polarity score, sense, and semantic features assist in identifying conceptual and sentiment relations from the corpus. The lexicon and all these features provide an essential support to analyze an unstructured corpus and represent it in a structured corpus which we term MediConceptNet: the medical concepts are connected with each other through the concerned features. A previously suggested network for the same purpose, e.g., SemNet, is only based on the semantic and affinity features. The semantic relations of the concepts can be successfully determined in three distinct ranges, e.g., 0 for no relation, 0-1 for partial relations, and 1 corresponding a full relation. To evaluate the data of MediConceptNet, we apply an agreement analysis provided by the Cohen’s kappa coefficient and achieve 0.66 agreement score, evaluating the comparative statistics of two medical practitioners working as manual an-
Intravenous tranexamic acid and intraoperative visualization during functional endoscopic sinus surgery: a double-blind randomized controlled trial.

BACKGROUND
Bleeding during endoscopic sinus surgery (ESS) can hinder surgical progress and may be associated with increased complications. Tranexamic acid is an antifibrinolytic that is known to reduce operative bleeding. The current study was designed to assess the effect of adjunctive intravenous tranexamic acid on intraoperative bleeding and the quality of the surgical field during ESS.


METHODS
Double-blind, randomized, controlled trial. Patients undergoing ESS for the primary diagnosis of chronic rhinosinusitis with or without polyposis were included. Sample size calculation based on a clinically relevant difference in the Wormald surgical field score yielded a sample of 28. In addition to standard measures to minimize blood loss, study patients received intravenous tranexamic acid with control patients receiving intravenous normal saline. Outcome measures included the Wormald grading scale to assess the intraoperative surgical field and estimated blood loss based on suction container contents with irrigation fluid subtracted.


RESULTS
Twenty-eight patients (median age, 45 years; range, 23-80 years) were included in the study. Diagnoses included chronic rhinosinusitis without polyposis (n = 5), chronic rhinosinusitis with polyposis (n = 23). The use of the tranexamic acid was not associated with a statistically significant decrease in estimated blood loss (201 vs 231 mL; p = 0.60) or Wormald grading scale (5.84 vs 5.80; p = 0.93). There were no adverse events or complications during the study.


CONCLUSION
Adjunctive intravenous tranexamic acid does not appear to result in a clinically meaningful reduction in blood loss or improve visualization of the surgical field during ESS.
Personality traits and concern for privacy: an empirical study in the context of location-based services

Received: 10 March 2008 Revised: 31 May 2008 2nd Revision: 27 July 2008 Accepted: 11 August 2008 Abstract For more than a century, concern for privacy (CFP) has co-evolved with advances in information technology. The CFP refers to the anxious sense of interest that a person has because of various types of threats to the person’s state of being free from intrusion. Research studies have validated this concept and identified its consequences. For example, research has shown that the CFP can have a negative influence on the adoption of information technology; but little is known about factors likely to influence such concern. This paper attempts to fill that gap. Because privacy is said to be a part of a more general ‘right to one’s personality’, we consider the so-called ‘Big Five’ personality traits (agreeableness, extraversion, emotional stability, openness to experience, and conscientiousness) as factors that can influence privacy concerns. Protection motivation theory helps us to explain this influence in the context of an emerging pervasive technology: location-based services. Using a survey-based approach, we find that agreeableness, conscientiousness, and openness to experience each affect the CFP. These results have implications for the adoption, the design, and the marketing of highly personalized new technologies. European Journal of Information Systems (2008) 17, 387–402. doi:10.1057/ejis.2008.29
Superpixel-Based Graphical Model for Remote Sensing Image Mapping

Object-oriented remote sensing image classification is becoming more and more popular because it can integrate spatial information from neighboring regions of different shapes and sizes into the classification procedure to improve the mapping accuracy. However, object identification itself is difficult and challenging. Superpixels, which are groups of spatially connected similar pixels, have the scale between the pixel level and the object level and can be generated from oversegmentation. In this paper, we establish a new classification framework using a superpixel-based graphical model. Superpixels instead of pixels are applied as the basic unit to the graphical model to capture the contextual information and the spatial dependence between the superpixels. The advantage of this treatment is that it makes the classification less sensitive to noise and segmentation scale. The contribution of this paper is the application of a graphical model to remote sensing image semantic segmentation. It is threefold. 1) Gradient fusion is applied to multispectral images before the watershed segmentation algorithm is used for superpixel generation. 2) A probabilistic fusion method is designed to derive node potential in the superpixel-based graphical model to address the problem of insufficient training samples at the superpixel level. 3) A boundary penalty between the superpixels is introduced in the edge potential evaluation. Experiments on three real data sets were conducted. The results show that the proposed method performs better than the related state-of-the-art methods tested.
A Survey of Augmented Reality Technologies , Applications and Limitations

— We are on the verge of ubiquitously adopting Augmented Reality (AR) technologies to enhance our perception and help us see, hear, and feel our environments in new and enriched ways. AR will support us in fields such as education, maintenance, design and reconnaissance, to name but a few. This paper describes the field of AR, including a brief definition and development history, the enabling technologies and their characteristics. It surveys the state of the art by reviewing some recent applications of AR technology as well as some known limitations regarding human factors in the use of AR systems that developers will need to overcome. I INTRODUCTION Imagine a technology with which you could see more than others see, hear more than others hear, and perhaps even touch, smell and taste things that others can not. What if we had technology to perceive completely computational elements and objects within our real world experience, entire creatures and structures even that help us in our daily activities , while interacting almost unconsciously through mere gestures and speech? With such technology, mechanics could see instructions what to do next when repairing an unknown piece of equipment, surgeons could see ultrasound scans of organs while performing surgery on them, fire fighters could see building layouts to avoid otherwise invisible hazards, soldiers could see positions of enemy snipers spotted by un-manned reconnaissance aircraft, and we could read reviews for each restaurant in the street we " re walking in, or battle 10-foot tall aliens on the way to work [57]. Augmented reality (AR) is this technology to create a " next generation, reality-based interface " [77] and is moving from laboratories around the world into various industries and consumer markets. AR supplements the real world with virtual (computer-generated) objects that appear to coexist in the same space as the real world. AR was recognised as an emerging technology of 2007 [79], and with today " s smart phones and AR browsers we are starting to embrace this very new and exciting kind of human-computer interaction. shino [107] (Fig. 1), AR is one part of the general area of mixed reality. Both virtual environments (or virtual reality) and augmented virtuality, in which real objects are added to virtual ones, replace the surrounding environment by a virtual one. In contrast, AR provides local virtuality. When considering not just artificiality but also user transportation, Benford et al. [28] …
Engineering response to the dual risk of natural hazards and global change

The research programs on natural hazards mitigation and in global change supported by the National Science Foundation are briefly described. The potential relationships between the two types of phenomena, natural and man made, are discussed together with a summary of possible future directions in engineering research.
Polyethylene glycol 4000 for treatment of functional constipation in children.

OBJECTIVES
The aim of the study was to evaluate the effectiveness and safety of 2 different polyethylene glycol (PEG) doses for the maintenance treatment of functional constipation in children.


METHODS
Children with functional constipation according to the Rome III criteria were randomly assigned to receive PEG 4000 at a dose of either 0.7 g/kg (high-dose group; n = 45) or 0.3 g/kg (low-dose group; n = 47) for 6 weeks. Adjustment of the therapy was recommended in the event of <3 bowel movements (BM) per week or ≥3 BM per day. The primary outcome measure was treatment success, defined as ≥3 BM per week with no fecal soiling during the last week of the intervention.


RESULTS
A total of 90 of 92 randomized children, with a mean age of 3.7 ± 2.1 years, completed the study. In the analysis based on allocated treatment, treatment success was similar in both groups (relative risk 0.9, 95% confidence interval 0.78-1.03). Compared with the high-dose PEG group, the low-dose PEG group had an increased need for therapy adjustment of borderline significance (relative risk 2.0, 95% confidence interval 1.0-4.2), an increased risk of painful defecation, a lower number of stools per week, and lower parental satisfaction. Adverse events were similar in both groups.


CONCLUSIONS
To achieve treatment success, both tested doses of PEG were equally safe and effective in the treatment of children with functional constipation.
A culturally and linguistically responsive vocabulary approach for young Latino dual language learners.

PURPOSE
This study examined the role of the language of vocabulary instruction in promoting English vocabulary in preschool Latino dual language learners (DLLs). The authors compared the effectiveness of delivering a single evidence-informed vocabulary approach using English as the language of vocabulary instruction (English culturally responsive [ECR]) versus using a bilingual modality that strategically combined Spanish and English (culturally and linguistically responsive [CLR]).


METHOD
Forty-two DLL Spanish-speaking preschoolers were randomly assigned to the ECR group (n=22) or CLR group (n=20). Thirty English words were presented during small-group shared readings in their preschools 3 times a week for 5 weeks. Multilevel models were used to examine group differences in postinstruction scores on 2 Spanish and 2 English vocabulary assessments at instruction end and follow-up.


RESULTS
Children receiving instruction in the CLR bilingual modality had significantly higher posttest scores (than those receiving the ECR English-only instruction) on Spanish and English vocabulary assessments at instruction end and on the Spanish vocabulary assessment at follow-up, even after controlling for preinstruction scores.


CONCLUSIONS
The results provide additional evidence of the benefits of strategically combining the first and second language to promote English and Spanish vocabulary development in this population. Future directions for research and clinical applications are discussed.
Post-bond Testing of the Silicon Interposer and Micro-bumps in 2.5D ICs

2.5D integration is emerging as a precursor to stacked 3D ICs. Since the silicon interposer and micro-bumps in 2.5D integration can suffer from fabrication and assembly defects, post-bond testing is necessary for product qualification. This paper proposes and evaluates an interposer test architecture based on extensions to the IEEE 1149.1 Std. The proposed method enables access to interconnects inside the interposer by probing on the C4 bumps. It provides an effective test method for opens, shorts, and interconnect delay fault in the interposer. Moreover, micro-bumps can be tested through test paths that include dies on the interposer. HSPICE simulation results show that a large range of defects can be detected, diagnosed, and characterized using the proposed approach.