Miracle-dz/UniFAR-FTUs huggingface dataset:
A Systematic Review of Substance Use (Disorder) in Individuals with Mild to Borderline Intellectual Disability

Although the attention for substance use (SU) and SU disorders (SUD) among individuals with mild to borderline intellectual disability (MBID) has been growing exponentially, this form of dual diagnosis has largely been ignored by addiction medicine. In this article, we systematically review the research between January 2000 and June 2018 on the prevalence, assessment, and treatment of SU(D) among children, adolescents, and adults with MBID. A total of 138 articles were included. It is concluded that individuals with MBID are likely to be at a higher risk for developing SUD compared to those without MBID. Future research should focus on the detection of MBID among patients being treated in addiction medicine, the development and implementation of systematic assessment methods of SU(D) among individuals with MBID, and the development and evaluation of prevention and treatment interventions. System integration, interdisciplinary collaboration, and the development of tailored treatment for individuals with MBID are advised to improve treatment access and outcome for those who have developed SUD.
Predicting and Testing Bioavailability of Magnesium Supplements

Despite the presumption of the beneficial effects of magnesium supplementation, little is known about the pharmacokinetics of different magnesium formulations. We aimed to investigate the value of two in vitro approaches to predict bioavailability of magnesium and to validate this in subsequent in vivo testing. In vitro assessment of 15 commercially available magnesium formulations was performed by means of a Simulator of the Human Intestinal Microbial Ecosystem (SHIME®) and by dissolution tests. Two magnesium formulations with contrasting bioavailability prediction from both in vitro tests (best vs. worst) were selected for in vivo testing in 30 subjects. In vivo bioavailability was compared following one acute ingestion by monitoring blood magnesium concentrations up to 6 h following intake. The in vitro tests showed a very wide variation in absorption and dissolution of the 15 magnesium products. In the in vivo testing, a significant different serum magnesium absorption profile was found up to 4 h following supplement ingestion for the two supplements with opposing in vitro test results. Moreover, maximal serum magnesium increase and total area under the curve were significantly different for both supplements (+6.2% vs. +4.6% and 6.87 vs. 0.31 mM.min, respectively). Collectively, poor bioaccessibility and bioavailability in the SHIME model clearly translated into poor dissolution and poor bioavailability in vivo. This provides a valid methodology for the prediction of in vivo bioavailability and effectiveness of micronutrients by specific in vitro approaches.
Mean-field theory of recurrent cortical networks: Working memory circuits with irregularly spiking neurons

Recent advances in neurophysiology have permitted the development of biophysically-realistic models of local recurrent cortical networks. These models have proved to be valuable for investigating the cellular and network mechanisms of information processing and memory in cortical microcircuits. Recurrent network models of spiking neurons are highly non-linear and display a variety of interesting dynamical behaviors, such as spatially organized firing patterns, synchronous oscillations or coexistence of multiple attractor states. It is notoriously hard to predict, solely by intuition, the behavior of such networks. Moreover, these large-scale network models routinely consist of many thousands of spiking neurons, so their computer simulations are timeconsuming. Therefore, it is highly desirable to develop and mathematically analyze simplified yet faithful ‘mean-field’ theories that are derived from these biophysically-based models. In this chapter, we review the mean-field theory of recurrent cortical network models in which neurons discharge spikes stochastically with high variability and interact with each other via biologically realistic synapses. Using the theory, models of working memory (active short-term memory) are discussed.
Whole grain and cereal fiber intake and the risk of type 2 diabetes: a meta-analysis.

In recent years, cardiovascular diseases (CVDs) have become a focus topic and global concern. There have been mixed reports on the relationship between whole grain or cereal fiber intake and the risk of type 2 diabetes. To evaluate whole grain or cereal intake on the risk of type 2 diabetes, we collected related literature on the relationship between whole grain or cereal fiber intake and the risk of type 2 diabetes. Methods: Eligible studies were identified from PubMed, Web of Science, and EBSCO (from 2007 to 2015). A total of three studies on whole grains were included, three studies about cereal fiber, and two on both whole grains and cereal fiber. We calculated the summary relative risks (RRs) using the random effects model. Eight studies contained 14,728 type 2 diabetes cases out of 434,903 subjects. Whole grain or cereal fiber intake is associated with type 2 diabetes (the overall RR was 0.68; 95% CI was 0.64-0.73) with significant heterogeneity in study-specific estimates (I2 =0%, P=0.452). Whole grain and cereal fiber intake are inversely associated with the risk of type 2 diabetes.
Effects of Single Cage Housing on Stress, Cognitive, and Seizure Parameters in the Rat and Mouse Pilocarpine Models of Epilepsy

Visual Abstract Many experimental approaches require housing rodents in individual cages, including in epilepsy research. However, rats and mice are social animals; and individual housing constitutes a stressful situation. The goal of the present study was to determine the effects of individual housing as compared to conditions maintaining social contact on stress markers and epilepsy. Control male mice socially housed during pretest and then transferred to individual cages for six weeks displayed anhedonia, increased anxiety and biological markers of stress as compared to pretest values or mice kept socially housed during six weeks. Pilocarpine (pilo)-treated mice housed together showed increased levels of anhedonia, anxiety and stress markers as well as decreased cognitive performance as compared to the control group. The differences were more significant in pilo-treated mice housed individually. Anxiety correlated linearly with cognitive performance and stress markers independently of the experimental conditions. In the male rat pilo model, seizures were sixteen times more frequent in singly housed animals as compared to animals kept in pairs. Daily interactions with an experimenter in otherwise singly housed animals was sufficient to produce results identical to those found in animals kept in pairs. We propose that social isolation produces a severe phenotype in terms of stress and seizure frequency as compared to animals maintaining social contact (at least in these two models), a factor that needs to be taken into account for data interpretation, in particular for preclinical studies.
Self-Healing Concrete Using Rubber Particles to Immobilize Bacterial Spores

Bacteria-based self-healing concrete is a construction material used to repair cracks in concrete, in which the bacterial spores are immobilized by bacteria carriers. However, the currently available bacteria carriers are not always suitable due to a complicated procedure or high cost. To develop a more suitable bacteria carrier as well as improve the anti-crack capability of self-healing concrete, in this study we evaluate the feasibility of using rubber particles as a novel bacteria carrier in self-healing concrete. Two types of self-healing concrete are prepared with rubber particles of different sizes to quantify the crack-healing effect. In addition, the fluidity and mechanical properties of the self-healing rubber concrete are compared with those of plain concrete and normal rubber concrete. The experimental results show that the self-healing rubber concrete with a particle size of 1~3 mm has a better healing capacity than the self-healing rubber concrete with a particle size of 0.2~0.4 mm, and the width value of the completely healed crack is 0.86 mm. The self-healing rubber concrete has a higher slump than the plain concrete and normal rubber concrete. According to the strength tests, the compressive strengths of the self-healing rubber concrete are low early on but they exceed those of the corresponding normal rubber concrete at 28 days. Moreover, the self-healing rubber concrete has higher splitting tensile strengths than the plain concrete and a better anti-crack capability. The results of a comparison to the other two representative bacterial carriers indicate that rubber particles have potential to be a widely used bacteria carrier for practical engineering applications in self-healing concrete.
Short-Term Retention of Location-Identity Bindings for Complex Objects

Knowing what is where is an essential and complex component of human perception. This ability refers to the concept of Situation Awareness (SA). The underlying mechanisms for this ability show parallels to the tracking of a set of identical objects moving on a screen, a theory known as Multiple Object Tracking (MOT) (Pylyshyn & Storm, 1988). This theory was useful for investigating the fundamental factors of visual tracking, but lacked a connection to real-world scenarios. In an attempt to bridge that gap, Oksama and Hyönä (2008) created the Model of Multiple Identity Tracking (MOMIT), which includes unique identities for each object being tracked and posits a combination of peripheral and focal perception in tracking, as opposed to strictly peripheral in the MOT paradigm. This model was then applied to air traffic control (ATC) displays to create a predictive utility for analyzing controllers’ performance (Hope, Rantanen, & Oksama, 2010). However, the call sign objects used in the MIT application study (Hope et al., 2010) only required the observer to remember a single letter from the object’s identity, negating the need to memorize the entire identity. Using a similar structure of typical ATC call signs (6-7 character alphanumeric strings), the experiment investigated the study time duration necessary to acquire and retain the identity and location information of complex objects, and in effect, form a level 1 SA. Furthermore, the accuracy of the location-identity bindings formed in level 1 SA are also investigated for various object set sizes (4, 8, or 12 objects). The object array size of 4 had the highest accuracy. As the object set size increased from 4 objects to 12 objects, the error in location information and identity information increased. Finally, it was found that approximately 3 complex ATC-like objects were retained by participants in all conditions.
Effect of advanced maternal age on pregnancy outcomes: a single-centre data from a tertiary healthcare hospital

Abstract The aim of this study was to assess the effect of advanced maternal age on pregnancy and neonatal outcomes in patients attending a tertiary centre hospital. Between January 2013 and December 2016, the records of all patients who were referred for pregnancy follow-ups and delivery were retrospectively reviewed and were divided according to their parity and age. Patients over 35 years old were categorised as advanced maternal age; (1) 35–40 years old. (2) 40–45 years old. (3) 45 years and over. Most of the prenatal complications were found to increase in the advanced maternal age group. The caesarian section rate was found to be higher in all advanced maternal age groups. There was no significant relationship between 5 Minute Apgar scores of <7 and perinatal mortality and post-term pregnancy and parity. Globally, advanced maternal age pregnancy shows an increase as a result pregnancy complication will increase. It is important to make a appropriate follow-up for pregnancies of advance maternal age mothers. Impact statement What is already known on this subject? Advanced maternal age is a poor prognostic factor for pregnancy outcomes. But there remains no consensus opinion or a plan for the management of pregnancy in this particular risk group. What do the results of this study add? This clinical study makes a contribution to the literature for advanced maternal age and pregnancy complications. This study is one of the few studies emphasising the importance of parity in advanced maternal age and the relationship between first trimester pregnancy complications and advanced maternal age. What are the implications of these findings for clinical practice and/or further research? After the ART pregnancies increasing all around the world not only advanced age but the parity become an important role. Due to an increase in advanced maternal age pregnancies in all around the world, we think that better understanding and management of the complications to be encountered in advanced maternal age and parity pregnancies will be appropriate.
Synthetic lethality between BRCA1 deficiency and poly(ADP-ribose) polymerase inhibition is modulated by processing of endogenous oxidative DNA damage

Abstract Poly(ADP-ribose) polymerases (PARPs) facilitate the repair of DNA single-strand breaks (SSBs). When PARPs are inhibited, unrepaired SSBs colliding with replication forks give rise to cytotoxic double-strand breaks. These are normally rescued by homologous recombination (HR), but, in cells with suboptimal HR, PARP inhibition leads to genomic instability and cell death, a phenomenon currently exploited in the therapy of ovarian cancers in BRCA1/2 mutation carriers. In spite of their promise, resistance to PARP inhibitors (PARPis) has already emerged. In order to identify the possible underlying causes of the resistance, we set out to identify the endogenous source of DNA damage that activates PARPs. We argued that if the toxicity of PARPis is indeed caused by unrepaired SSBs, these breaks must arise spontaneously, because PARPis are used as single agents. We now show that a significant contributor to PARPi toxicity is oxygen metabolism. While BRCA1-depleted or -mutated cells were hypersensitive to the clinically approved PARPi olaparib, its toxicity was significantly attenuated by depletion of OGG1 or MYH DNA glycosylases, as well as by treatment with reactive oxygen species scavengers, growth under hypoxic conditions or chemical OGG1 inhibition. Thus, clinical resistance to PARPi therapy may emerge simply through reduced efficiency of oxidative damage repair.
Hip and Wrist-Worn Accelerometer Data Analysis for Toddler Activities

Although accelerometry data are widely utilized to estimate physical activity and sedentary behavior among children age 3 years or older, for toddlers age 1 and 2 year(s), accelerometry data recorded during such behaviors have been far less examined. In particular, toddler’s unique behaviors, such as riding in a stroller or being carried by an adult, have not yet been examined. The objective of this study was to describe accelerometry signal outputs recorded during participation in nine types of behaviors (i.e., running, walking, climbing up/down, crawling, riding a ride-on toy, standing, sitting, riding in a stroller/wagon, and being carried by an adult) among toddlers. Twenty-four toddlers aged 13 to 35 months (50% girls) performed various prescribed behaviors during free play in a commercial indoor playroom while wearing ActiGraph wGT3X-BT accelerometers on a hip and a wrist. Participants’ performances were video-recorded. Based on the video data, accelerometer data were annotated with behavior labels to examine accelerometry signal outputs while performing the nine types of behaviors. Accelerometer data collected during 664 behavior assessments from the 21 participants were used for analysis. Hip vertical axis counts for walking were low (median = 49 counts/5 s). They were significantly lower than those recorded while a toddler was “carried” by an adult (median = 144 counts/5 s; p < 0.01). While standing, sitting, and riding in a stroller, very low hip vertical axis counts were registered (median ≤ 5 counts/5 s). Although wrist vertical axis and vector magnitude counts for “carried” were not higher than those for walking, they were higher than the cut-points for sedentary behaviors. Using various accelerometry signal features, machine learning techniques showed 89% accuracy to differentiate the “carried” behavior from ambulatory movements such as running, walking, crawling, and climbing. In conclusion, hip vertical axis counts alone may be unable to capture walking as physical activity and “carried” as sedentary behavior among toddlers. Machine learning techniques that utilize additional accelerometry signal features could help to recognize behavior types, especially to differentiate being “carried” from ambulatory movements.
Gaussian Processes For Machine Learning

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided.
Science for real life : the use of case studies and online discussions in high school anatomy and physiology

Students in post-secondary health care programs often utilize case studies as a mechanism for learning and reinforcing content. In addition, students are increasingly taking courses online. Therefore, an action research-based project was undertaken in a high school anatomy and physiology course to identify the impact of case studies and online discussions on content acquisition, student interest and engagement. Two treatment methods were employed across three separate sections of grade twelve anatomy and physiology classes. One treatment included the implementation of case studies entirely in class, while the second treatment duplicated the first treatment but included additional case analysis via online discussions outside of class time. The results suggest that students can acquire new content through the use of case studies and that students generally enjoy and find case studies to be an interesting learning method. In addition, while overall student perceptions of using online discussions were negative, overall student test scores across all three case studies were higher, on average, in the treatment group that included online discussions.
Review on tools for image detection forgery

This paper defines the presently used methods and approaches in the domain of digital image forgery detection. A survey of a recent study is explored including an examination of the current techniques and passive approaches in detecting image tampering. This area of research is relatively new and only a few sources exist that directly relate to the detection of image forgeries. Fake images have become widespread in society today. The accessibility to powerful simple to use image editing computer software to end users helps make the job of manipulating image incredibly easy. One can find forged images used to sensationalize news, spread political propaganda and rumors, introduce psychological bias, etc. in all forms of media.
Method of High Accuracy Pseudorange Generation for Real-time High Dynamic GNSS Signal Simulator

Increasing the accuracy of pseudorange(PR) generation is one of the key technologies in developing real-time high dynamic globol navigation satellite system(GNSS) signal simulator.In this work,the proposed method takes user trajectory coordinates as input,and uses Keplerian parameters to calculate satellite positions for constellation simulation and parameter generation.To achieve high accuracy true range,the coordinate differences due to ECEF rotation should be considered during iterative calculation of PR.For PR generation,a cubic spline based algorithm is proposed to calculate the 3rd order PR polynomial coefficients directly.Above measures avoid the complexity and inaccuracy in existing algorithms which need to calculate satellite-user line-of-sight dynamic parameters such as high order derivatives for PR errors,satellite positions and user position respectively.Simulation result shows that the fitting error of proposed method is below 0.1 mm.
Access to Successful Language Learning: A Review of the Book Language Learning Strategies-What Every Teacher Should Know

This paper first introduces a classic book on language learning strategies written by Rebeccal L.Oxford, that is, Language Learning Strategies——What Every Teacher Should Know (English edition), and then makes some criticism on this book. Because at present there is still disagreement on the taxonomy of learning strategies, this paper then expounds the taxonomy used in this book and analyzes its advantages as well as disadvantages. Finally, on the basis of achievements and practice related to learning strategies and that of TCFL, this paper suggests the reevaluation of the effect of different learning strategies in terms of Chinese characteristics and the combination of learning strategy training with formal classroom instruction in TCFL.
Discrete Search Leading Continuous Exploration for Kinodynamic Motion Planning

This paper presents the Discrete Search Leading continuous eXploration (DSLX) planner, a multi-resolution approach to motion planning that is suitable for challenging problems involving robots with kinodynamic constraints. Initially the method decomposes the workspace to build a graph that encodes the physical adjacency of the decomposed regions. This graph is searched to obtain leads, that is, sequences of regions that can be explored with sampling-based tree methods to generate solution trajectories. Instead of treating the discrete search of the adjacency graph and the exploration of the continuous state space as separate components, DSLX passes information from one to the other in innovative ways. Each lead suggests what regions to explore and the exploration feeds back information to the discrete search to improve the quality of future leads. Information is encoded in edge weights, which indicate the importance of including the regions associated with an edge in the next exploration step. Computation of weights, leads, and the actual exploration make the core loop of the algorithm. Extensive experimentation shows that DSLX is very versatile. The discrete search can drastically change the lead to reflect new information allowing DSLX to find solutions even when sampling-based tree planners get stuck. Experimental results on a variety of challenging kinodynamic motion planning problems show computational speedups of two orders of magnitude over other widely used motion planning methods.