Miracle-dz/UniFAR-FTUs huggingface dataset:
Pharmaceutical Dispersion Techniques for Dissolution and Bioavailability Enhancement of Poorly Water-Soluble Drugs

Over the past decades, a large number of drugs as well as drug candidates with poor dissolution characteristics have been witnessed, which invokes great interest in enabling formulation of these active ingredients. Poorly water-soluble drugs, especially biopharmaceutical classification system (BCS) II ones, are preferably designed as oral dosage forms if the dissolution limit can be broken through. Minimizing a drug’s size is an effective means to increase its dissolution and hence the bioavailability, which can be achieved by specialized dispersion techniques. This article reviews the most commonly used dispersion techniques for pharmaceutical processing that can practically enhance the dissolution and bioavailability of poorly water-soluble drugs. Major interests focus on solid dispersion, lipid-based dispersion (nanoencapsulation), and liquisolid dispersion (drug solubilized in a non-volatile solvent and dispersed in suitable solid excipients for tableting or capsulizing), covering the formulation development, preparative technique and potential applications for oral drug delivery. Otherwise, some other techniques that can increase the dispersibility of a drug such as co-precipitation, concomitant crystallization and inclusion complexation are also discussed. Various dispersion techniques provide a productive platform for addressing the formulation challenge of poorly water-soluble drugs. Solid dispersion and liquisolid dispersion are most likely to be successful in developing oral dosage forms. Lipid-based dispersion represents a promising approach to surmounting the bioavailability of low-permeable drugs, though the technique needs to traverse the obstacle from liquid to solid transformation. Novel dispersion techniques are highly encouraged to develop for formulation of poorly water-soluble drugs.
"I'm Never Happy with What I Write": Challenges and Strategies of People with Dyslexia on Social Media

This work studies the experiences, challenges, and strategies of people with dyslexia when using social media. We interviewed 11 people with dyslexia to understand their gen- eral experiences with reading and writing content on Facebook. The interview study findings highlight the challenges they face when writing content on Social Networking Sites (SNSs), and their strategies for mitigating these challenges. Following up on this, we surveyed 492 participants, among whom 67 self-reported as having dyslexia. The survey results confirm challenges with and strategies for writing unique to people with dyslexia, although they also suggest that better writing support on SNSs may be more broadly beneficial.
Muslim Husbands’ Roles in Women’s Health and Cancer: The Perspectives of Muslim Women in Indonesia

Background: Breast and cervical cancers are the most common cause of cancer death among women in the world. These cancers are detectable early, however only a few women participate in cancer screening especially in developing countries, including Indonesia. Family, culture and religion can influence why women have screening. Husbands, in Muslim families have a significant role in the family’s health including their wife’s reproductive health. However, information about Muslim husbands’ roles in wife’s health especially cancer is limited. Objective: The purpose of this study was to determine Muslim husband’s roles in women’s health and cancer from the perspectives of Muslim women. Methods: This study was a qualitative study using a descriptive exploratory approach. Purposive sampling was used to recruit 20 Muslim women, 10 from urban areas and 10 from rural areas of West Java Province, Indonesia. Women were interviewed using a semi-structured interview schedule. Data from the interviews were analyzed using the Comparative Analysis for Interview technique. Results: The study found two main themes emerged from the analysis: Muslim husbands’ extensive roles in promoting women’s health and Husbands’ have limited actions with regard to cancer screening. This study also found similarities between rural and urban women’s opinions that in general husbands actively supported promoting women’s health. Conclusion: Muslim husbands focused on encouraging women to have healthy lifestyles, however, a lack of support from husbands related to cancer screening. This behaviour could be a hindrance to Muslim women’s participation in prevention and the early detection of cancer. There is a need to improve Muslim husbands’ awareness in women’s cancer.
Chronic pancreatitis: review and update of etiology, risk factors, and management

Chronic pancreatitis is a syndrome involving inflammation, fibrosis, and loss of acinar and islet cells which can manifest in unrelenting abdominal pain, malnutrition, and exocrine and endocrine insufficiency. The Toxic-Metabolic, Idiopathic, Genetic, Autoimmune, Recurrent and Severe Acute Pancreatitis, Obstructive (TIGAR-O) classification system categorizes known causes and factors that contribute to chronic pancreatitis. Although determining disease etiology provides a framework for focused and specific treatments, chronic pancreatitis remains a challenging condition to treat owing to the often refractory, centrally mediated pain and the lack of consensus regarding when endoscopic therapy and surgery are indicated. Further complications incurred include both exocrine and endocrine pancreatic insufficiency, pseudocyst formation, bile duct obstruction, and pancreatic cancer. Medical treatment of chronic pancreatitis involves controlling pain, addressing malnutrition via the treatment of vitamin and mineral deficiencies and recognizing the risk of osteoporosis, and administering appropriate pancreatic enzyme supplementation and diabetic agents. Cornerstones in treatment include the recognition of pancreatic exocrine insufficiency and administration of pancreatic enzyme replacement therapy, support to cease smoking and alcohol consumption, consultation with a dietitian, and a systematic follow-up to assure optimal treatment effect.
Qualitative configuration based on generality data in ranch in three-river headwaters region

Three-River Headwaters Region is the complex ecosystem with typical characteristics of alpine grass land. Livestock husbandry is the main industry of yak husbandry. In recent years, with the continuous advance of industry 4.0, the data in the alpine animal husbandry has the problems of low standardization and low clustering. It can not be applied to the rapid development of pasture intelligence. Therefore, it is necessary to establish qualitative configuration model for the generality data of alpine grassland. In this study, it builds the relevant model and data model framework bases on the main characteristics of grass production and yak habit. The model is solved by the linear regression algorithm and the genetic algorithm(GA). The experimental results offer reliable reference value for the research of related science. It also settles the corresponding technical support for the rapid development of intelligent animal husbandry.
Boosted non-linear and non-negative sparse learning for single image super-resolution

In image super-resolution area, the effectiveness of sparse learning methods have been demonstrated, especially in single image super-resolution applications. A novel sparse learning method is proposed in this paper for the task of single image super-resolution. The proposed non-linear and nonnegative sparsity-based learning model is used to capture the nonlinear data distributions in images. Moreover, a boosting ensemble strategy is used to improve the learned ‘weak’ sparse model. In each round of boosting, the training images are chosen according to the reconstruction errors of the learned models from previous rounds. The obtained dictionary ensemble contains dictionaries which have different reconstruction capability on different types of image patches. Then the support vector regression is applied for obtaining the final result image. The proposed non-negative kernel sparse model was tested on popular benchmark images, the experimental results illustrate the competitiveness of the proposed method.
Metformin in the management of diabetes during pregnancy and lactation

This review explores the current place of metformin in the management of gestational diabetes (GDM) and type 2 diabetes during pregnancy and lactation. The rationale and basic pharmacology of metformin usage in pregnancy is discussed along with the evidence from observational and randomized controlled trials in women with GDM or overt diabetes. There seems to be adequate evidence of efficacy and short-term safety of metformin in relation to maternal and neonatal outcomes in GDM, with possible benefits related to lower maternal weight gain and lower risk of neonatal hypoglycemia and macrosomia. Additionally, metformin offers the advantages of oral administration, convenience, less cost and greater acceptability. Metformin may, therefore, be considered in milder forms of GDM where glycemic goals are not attained by lifestyle modification. However, failure rate is likely to be higher in those with an earlier diagnosis of GDM, higher blood glucose, higher body mass index (BMI) or previous history of GDM, and insulin remains the cornerstone of pharmacological treatment in such cases. The use of metformin in type 2 diabetes has been assessed in observational and small randomized trials. Metformin monotherapy in women with overt diabetes is highly unlikely to achieve glycemic targets. Hence, the use should be restricted as adjunct to insulin and may be considered in women with high insulin dose requirements or rapid weight gain. There is clearly a need for more clinical trials to assess the effect of combined insulin plus metformin therapy in pregnancy with type 2 diabetes. Additionally, there is a paucity of data on long-term effects in offspring exposed to metformin in utero. It is imperative to further explore its impact on offspring as metformin has significant transplacental transfer and has the potential to impact the programming of the epigenome. Therefore, caution must be exercised when prescribing metformin in pregnant women. More research is clearly needed before metformin can be considered as standard of care in the management of diabetes during pregnancy.
Duty-cycle-accelerated hot-carrier degradation and lifetime evaluation for 700V lateral DMOS

Due to serious self-heating effect, traditional DC stress is hard to be used for evaluating the hot-carrier degradation of the LDMOS above 600V. In this work, the hot-carrier degradation for a 724V-breakdown LDMOS is studied by adopting gate duty-cycle-accelerated AC stress. It demonstrates that hot-electrons injection and donor-like interface states generation happen near the drain when the gate pulse is high. No obvious degradation and recovery can be observed when the gate pulse is zero. Moreover, the short pulse edges enhance the decrease of on-resistance (Ron) due to transient hot-holes injection into bird's beak. The device lifetime is also calculated according to the proposed models related to duty-cycle.
Sleeping tongue: current perspectives of genioglossus control in healthy individuals and patients with obstructive sleep apnea

The focus of this review was on the genioglossus (GG) muscle and its role in maintaining upper airway patency in both healthy individuals and obstructive sleep apnea (OSA) patients. This review provided an overview of GG anatomy and GG control and function during both wakefulness and sleep in healthy individuals and in those with OSA. We reviewed evidence for the role of the GG in OSA pathogenesis and also highlighted abnormalities in GG morphology, responsiveness, tissue movement patterns and neurogenic control that may contribute to or result from OSA. We summarized the different methods for improving GG function and/or activity in OSA and their efficacy. In addition, we discussed the possibility that assessing the synergistic activation of multiple upper airway dilator muscles may provide greater insight into upper airway function and OSA pathogenesis, rather than assessing the GG in isolation.
Evaluating genomic signatures of “the large X‐effect” during complex speciation

The ubiquity of the “two rules of speciation”—Haldane's rule and the large X‐effect—implies a general, special role for sex chromosomes in the evolution of intrinsic postzygotic reproductive isolation. The recent proliferation of genome‐scale analyses has revealed two further general observations: (a) complex speciation involving some form of gene flow is not uncommon, and (b) sex chromosomes in male‐ and in female‐heterogametic taxa tend to show elevated differentiation relative to autosomes. Together, these observations are consistent with speciation histories in which population genetic differentiation at autosomal loci is reduced by gene flow while natural selection against hybrid incompatibilities renders sex chromosomes relatively refractory to gene flow. Here, I summarize multilocus population genetic and population genomic evidence for greater differentiation on the X (or Z) vs. the autosomes and consider the possible causes. I review common population genetic circumstances involving no selection and/or no interspecific gene flow that are nevertheless expected to elevate differentiation on sex chromosomes relative to autosomes. I then review theory for why large X‐effects exist for hybrid incompatibilities and, more generally, for loci mediating local adaptation. The observed levels of sex chromosome vs. autosomal differentiation, in many cases, appear consistent with simple explanations requiring neither large X‐effects nor gene flow. Discerning signatures of large X‐effects during complex speciation will therefore require analyses that go beyond chromosome‐scale summaries of population genetic differentiation, explicitly test for differential introgression, and/or integrate experimental genetic data.
Chronic Pain and Selective Attention to Pain Arousing Daily Activity Pictures: Evidence From an Eye Tracking Study

Introduction: According to the pain research literature, attentional bias for pain is the mechanism responsible for the development and maintenance of fear of pain in patients with chronic pain. However, there is still some debate about the exact mechanism and the role of faster engagement versus difficulty in disengagement in the development of attentional bias. Methods: To investigate attentional bias in patients with chronic pain, we used an eye-tracker with the pictures of pain-provoking activities and compared the results with an age- and gender-matched group of pain-free participants. In addition, other measures of pain-related cognition and pain severity ratings were included to assess their contribution to the attentional bias toward pain-related information. Results: Calculating the frequency of the first fixations showed that both groups fixated initially on pain-provoking pictures compared to neutral one. Calculating the speed of fixations showed that control participants were faster in fixating on neutral stimuli, but patients with pain were faster in fixating on pain-provoking pictures, indicating a relative vigilance for the pain-related stimuli among them. These patients reported that the intensity of pain in the previous week was positively correlated with the speed of their fixation on the painful stimuli. Conclusion: Although these results did not provide unequivocal support for the vigilance-avoidance hypothesis, they are generally consistent with the results of studies using eye tracking technology. Furthermore, our findings put a question over characterization of attentional biases in patients with chronic pain by simply relating that to difficulty in disengaging from pain-related stimuli.
Saliency detection: Multi-level combination approach via graph-based manifold ranking

In this paper, we form the saliency map by a multi-level combination approach using graph-based manifold ranking method as the foundation. This method aims to overcome the defects that the merely graph-based manifold ranking method can not do well in highlighting the salient objects uniformly and suppressing the background effectively. We first execute over-segmentation algorithm for each input image. In order to take full advantages of the image cues, input image is segmented into multilevels from the coarsest to the finest in terms of the number of segmented regions. And for each level, graph-based manifold ranking approach is used to produce the initial saliency map. Then we obtain the optimal weight of each level from the trained combiner to make a multi-level combination to obtain the final saliency map. The combiner is trained using quadratic programming algorithm on the MSRA-10K database. In the experiment, we compare our method with the other eight state-of-the-art methods according to four evaluation criteria. The experimental results show that the proposed algorithm achieves favorable performance compared with the other eight state-of-the-art approaches on different databases.
Active Learning with Unbalanced Classes and Example-Generation Queries

Machine learning in real-world high-skew domains is difficult, because traditional strategies for crowdsourcing labeled training examples are ineffective at locating the scarce minority-class examples. For example, both random sampling and traditional active learning (which reduces to random sampling when just starting) will most likely recover very few minority-class examples. To bootstrap the machine learning process, researchers have proposed tasking the crowd with finding or generating minority-class examples, but such strategies have their weaknesses as well. They are unnecessarily expensive in well-balanced domains, and they often yield samples from a biased distribution that is unrepresentative of the one being learned.This paper extends the traditional active learning framework by investigating the problem of intelligently switching between various crowdsourcing strategies for obtaining labeled training examples in order to optimally train a classifier. We start by analyzing several such strategies (e.g., annotate an example, generate a minority-class example, etc.), and then develop a novel, skew-robust algorithm, called MB-CB, for the control problem. Experiments show that our method outperforms state-of-the-art GL-Hybrid by up to 14.3 points in F1 AUC, across various domains and class-frequency settings.
What interventions reduce the risk of contrast nephropathy for high-risk patients?

■ Evidence-Based Answer Several interventions may reduce the risk of contrast nephropathy for high-risk patients; however, most evidence uses surrogate markers for clinically relevant outcomes. Because dehydration is a risk factor for developing contrast nephropathy, periprocedural hydration is routinely recommended (strength of recommendation [SOR]: C, expert opinion). Single studies have suggested that isotonic saline is associated with less risk than half-normal saline, and hydration with fluids containing sodium bicarbonate is more efficacious than those containing isotonic saline (SOR: B, single randomized controlled trial [RCT]). Oral acetylcysteine lowers the risk of postcontrast elevations in creatinine if taken more than 24 hours before contrast administration (SOR: A, RCTs). Acetylcysteine’s low cost and favorable side effect profile make it an appealing option. Hypoosmolar contrast media are less likely to induce contrast nephropathy than hyper-osmolar media (SOR: A, RCTs). Finally, hemofiltration might be considered for patients with extremely high risk of developing contrast nephropathy (SOR: B, single RCT).
Quadcopter Modeling in Virtual Reality for Dynamic Visualization

This study presents an alternative approach to observe the works of the quadcopter control system through virtual reality display, in which real-time human-computer interactions are possible. By using Simulink software, the control systems are designed in form of three block diagrams with progressive complexity and programmed into a three-channel joystick. The first block diagram shows the translational movement according to the joystick behavior to move forward, backward, left, right, and throttle. The second block diagram is combined with the first diagram and added the rotational movement with maximum angle alteration of 57 degrees in each attitude movement. Continuous movement on circular trajectory was also analyzed to comprehend the correlation between the heading angle with the position vector. The third block diagram is the culmination of all diagrams and added the PID control to improve the stability in maneuver. The results show that the movement of quadcopter in virtual reality facilitate user to perceive the dynamic visualization of translational and rotational movement, thus it can also be of advantage for educational purpose. The integration of virtual reality and control system also reveal the vector position and generated angle, thus any possible error in the algorithm used can be precisely solved.
Performance Analysis of NOMA-Based Land Mobile Satellite Networks

Non-orthogonal multiple access (NOMA) scheme, which has the ability to superpose information in the power domain and serve multiple users on the same time/frequency resource, is regarded as an effective solution to increase transmit rate and fairness. In this paper, we introduce the NOMA scheme in a downlink land mobile satellite (LMS) network and present a comprehensive performance analysis for the considered system. Specifically, we first obtain the power allocation coefficients by maximizing the sum rate while meeting the predefined target rates of each NOMA user. Then, we derive the theoretical expressions for the ergodic capacity and the energy efficiency of the considered system. Moreover, the outage probability (OP) and average symbol error rate performances of NOMA users are derived analytically. To gain further insights, we derive the asymptotic OP at the high signal-to-noise ratio regime to characterize the diversity orders and coding gains of NOMA users. Finally, simulation results are provided to validate the theoretical analysis as well as the superiority of employing the NOMA scheme in the LMS system, and show the impact of key parameters, such as fading configurations and user selection strategy on the performance of NOMA users.
Evaluation of Gist Operator for Document Image Retrieval

As digitised documents normally contain a large variety of structures, a page segmentation- and layout-free method for document image retrieval is preferable. In this research work, therefore, wavelet transform as a transform-based approach is initially used to provide different under-sampled images from the original image. Then, Gist operator, as a feature extraction technique, is employed to extract a set of global features from the original image as well as the sub-images obtained from the wavelet transform. Moreover, the column-wise variances of the values in each sub-image are computed and they are then concatenated to obtain another set of features. Considering each feature set, locality-sensitive hashing is employed to compute similarity distances between a query and the document images in the database. Finally, a classifier fusion technique using the mean function is taken into account to provide a document image retrieval result. The combination of these features and a clustering score fusion strategy provides higher document image retrieval accuracy. Two different databases of the document image are considered for experimentation. The results obtained from the experimental study are detailed and the results are encouraging.