Miracle-dz/UniFAR-FTUs huggingface dataset:
Required HLB Determination of Some Pharmaceutical Oils in Submicron Emulsions

Different calculations of the hydrophilie-lipophilie balance (HLB) value of Sorbitan fatty acid ester are discussed in literature. Influence on the required HLB value of ethyl oleate was investigated using several emulsifier blends: Span 80/Tween 20, Oleth-3/Steareth-20, Oleth-5/Steareth-20, Oleth-3/PEG-40-Stearate. The calculations of the HLB value of Span 80 have a bearing influence on the determination of the required HLB value. The postulated transferability of the determined required HLB value by the Tween 20/Span 80 system compared to other emulsifier systems is depending on the used equation. Additionally, the required HLB values of the pharmaceutical oils coco-caprate/caprylate and cetearyl isononanoate were determined empirically by preparing submicron emulsions.
Selective Discovery of GPCR Ligands within DNA-Encoded Chemical Libraries Derived from Natural Products: A Case Study on Antagonists of Angiotensin II Type I Receptor.

Natural products have failed to meet the urgent need for drug discovery in recent decades due to limited resources, necessitating new strategies for re-establishing the key role of natural products in hit screening. This work introduced DNA-encoding techniques into the synthesis of phenolic acid-focused libraries containing 32 000 diverse compounds. Online selection of the library using immobilized angiotensin II type I receptor (AT1R) resulted in seven phenolic acid derivatives. The half-maximal concentration (IC50) of hit 1 for the right shift of the [125I]-Sar1-AngII competition curve was 19.6 nM. Pharmacological examination of renovascular hypertensive rats demonstrated that hit 1 significantly lowered the blood pressure of the animals without changing their heart rates. These results were used to create a general strategy for rapid and unbiased discovery of hits derived from natural products with high throughput and efficiency.
Using random assignment to measure court accessibility for low-income divorce seekers

Significance The United States faces an access-to-justice crisis: When the vast majority of individuals encounter the court system—when they face eviction or foreclosure, when they need restraining orders against abuse, when they are sued by debt collectors—they do so without a lawyer, frequently because they cannot afford one. This study exposes that the crisis is more pervasive and extreme than previously understood. Using randomization, it documents how a courthouse in one of the most progressive areas of the country remained largely inaccessible to divorce seekers without lawyers, even though the legal procedures for obtaining a dissolution of marriage—which is a constitutional right—were straightforward, ordinarily requiring little more than filing the right paperwork in the right order. We conducted a field experiment in which 311 low-income individuals seeking a divorce were randomly assigned to receive access to a pro bono lawyer (versus minimal help) to assist with filing for divorce. Examining court records, we found that assignment to an attorney made a large difference in whether participants filed for and obtained a divorce. Three years after randomization, 46% of the treated group had terminated their marriages in the proper legal venue, compared to 9% of the control group. Among “compliers”—participants who obtained representation only if assigned to receive it—those with lawyers were far more likely to file for and obtain a divorce than those not assigned lawyers. Because divorce implicates fundamental constitutional interests and can be effectuated only by resort to the courts, the US Constitution requires that dissolution of marriage be made achievable regardless of ability to pay. Yet, we observed few low-income individuals who were able to initiate divorce suits on their own. Through interviews and archival research, we identified barriers that low-income litigants faced in navigating the divorce system, including mandatory wait times, limited hours at important facilities, and burdensome paperwork sometimes requiring access to photocopiers and typewriters. This study therefore documents a salient instance in which a civil legal process was inaccessible to those without lawyers, even though their legal issues were straightforward, involving few if any matters for courts to adjudicate.
Electrolyte roadblocks to a magnesium rechargeable battery

Low cost, non-dendritic magnesium metal is an ideal anode for a post lithium ion battery. Currently, development of magnesium electrolytes governs the rate of progress in this field, because electrolyte properties determine the class of cathodes utilized. A review of the latest progress in the area of magnesium battery electrolyte and a perspective on mitigating present challenges is presented herein. Firstly, density functional theory has been shown to predict the potential window of magnesium electrolytes on inert electrodes. Secondly, we report initial efforts aimed to overcome the corrosive property of these magnesium organohaloaluminates towards less noble metals such as stainless steel. This is a major challenge in developing high voltage magnesium electrolytes essential for batteries which operate above 3V. We lastly touch on cathode candidates including the insertion and conversion classes. One conversion cathode we pay particular attention to is electrophilic sulfur which can be married with magnesium metal anodes by utilizing non-nucleophilic electrolytes obtained by simple crystallization of in situ generated magnesium organohaloaluminates. Effectively, non-nucleophilic electrolytes open the door to research on magnesium/sulfur batteries.
Differential Response to the High Doses of Dimethyl Sulfoxide of the Several Human Cancer Cell Lines Cultured in 2D Monolayer, Decellularized Matrix, and 3D Spheroid cell Culture Systems

When using cell-based models for drug research screening it is of critical importance to validate their applicability and accuracy. Here we report that the patterns of cellular response to high concentrations of DMSO measured with vital dye are cell line-specific and varied in time and type of response for different cell lines and for the same cell line cultures in 2D Monolayer, Decellularized Matrix, or 3D Spheroid cell culture systems. This should be considered at the stage of the experimental design, and for each experiment the more suitable cell culture system should be chosen, based on the characteristics of cellular response to DMSO in this particular system, especially if developing cell-based automated systems for drug screening.
Using Hidden Markov Model for Identification Based on EEG Signals

The researches on individual identification approaches based on EEG signals draw lots of attention in recent years. Few of them got time-robust identification performance. In this study, we focused on the time robustness of individual identification using EEG under conditions of resting-state of eye open/closed (REO/REC). Ten subjects participated in this study and each of them conducted three independent runs experiment, with the time intervals between adjacent runs were at least two weeks. There were three sessions within each run, and the time duration of each session is 150 seconds of REO/REC. Two features, auto-regressive (AR) and Mel-frequency cepstrum coefficients (MFCC) were calculated as identity features. Then Support vector machines (SVM) and Hidden Markov model (HMM) were used as classifiers. To access the time-robust performance of our methods, we used one of three runs data as test set and the other two as training set. Results show that the best classification accuracy is 80%. It is believed that under the conditions of REC and REO, the identity features of most subjects are robust across time and can be used for identification. This study will have an important impact on in EEG-based identification system.
Effective Evaluation of Clustering Algorithms on Single-Cell CNA data

Clustering methods are increasingly applied to single-cell DNA sequencing (scDNAseq) data to infer the subclonal structure of cancer. However, the complexity of these data exacerbates some data-science issues and affects clustering results. Additionally, determining whether such inferences are accurate and clusters re-capitulate the real cell phylogeny is not trivial, mainly because ground truth information is not available for most experimental settings. Here, by exploiting simulated sequencing data representing known phylogenies of cancer cells, we propose a formal and systematic assessment of well-known clustering methods to study their performance and identify the approach providing the most accurate reconstruction of phylogenetic relationships.
Body Size Is Related to Temperature Preference in Hyla chrysoscelis Tadpoles

Abstract. Temperature plays a critical role in growth and development of anurans. Here, we investigated thermal preference of tadpoles from a wide-ranging anuran, Hyla chrysoscelis, by establishing an ex situ thermal gradient in a laboratory setting. We collected 64 tadpoles with a mean (±SD) body length of 12.2 ± 2.1 mm (range, 7–15 mm). Mean temperature preference of tadpoles ranged from 12.9 to 30.0°C, and we found a positive relationship between temperature preference and body length. Although body length is only one component of amphibian development, its apparent link with temperature preference is an exciting area for further research in this species as well as other species. Furthermore, given the broad distribution of H. chrysoscelis, there is an opportunity to investigate how thermal preferences could limit population edges and how populations may respond to shifts in environmental temperatures.
Arboreal Prey-Handling of Endothermic Prey by Captive Boa Constrictors

Abstract. Prey-handling behavior serves as an important link between the processes of prey capture, transport, and swallowing. Snakes, lacking limbs, have developed a series of complex behaviors for the purposes of subjugating and handling their food. Using captive individuals of the semiarboreal Boa constrictor, we describe for the first time a set of behaviors unique to handling dead, endothermic prey in an arboreal context. Faced with the challenges of having to support the body weight of both themselves and their prey, Boa Constrictors create a series of loops that allow the body of the snake to support the prey item while also allowing for intraoral transport and swallowing. These loops can be adjusted and repositioned during transport, positioning the prey so that the pull of gravity is in line with swallowing.
Phylogeographic Origin of California Slender Salamanders (Batrachoseps attenuatus) in the Sutter Buttes

Abstract. The phylogeny of California Slender Salamanders (Batrachoseps attenuatus), which inhabits Northern California's Coast Ranges and Sierra Nevada foothills, was previously investigated by Martínez-Solano et al. (2007), who recovered a monophyletic species that contained five geographically cohesive major clades. However, a population isolate of B. attenuatus found in the Sutter Buttes, a geographically isolated volcanic mountain range within the Sacramento Valley, was not available in their phylogenetic analysis. We sequenced the ∼780-base pair segment of the mitochondrial DNA cytochrome b (cytb) gene used in Martínez-Solano et al. (2007) to examine the phylogenetic placement of this isolated population within the B. attenuatus complex. Our results, based on a single mitochondrial marker, indicate that the Sutter Buttes population of B. attenuatus is genetically distinct and falls within the Martínez-Solano et al. (2007) “East Bay/Sierra subclade” that, in turn, is nested within their “Eastern” major clade. Although we cannot accurately estimate how long the Sutter Buttes population has been isolated, B. attenuatus was likely able to colonize the Sutter Buttes during pluvial Pleistocene interglacials when more contiguous woodlands may have opened dispersal corridors across the Great Central Valley.
Development of an international template to support patient submissions in Health Technology Assessments

Abstract Objectives To develop an international template to support patient submissions in Health Technology Assessments (HTAs). This was to be based on the experience and feedback from the implementation and use of the Scottish Medicines Consortium's (SMC) Summary Information for Patient Groups (SIP). Methods To gather feedback on the SMC experience, web-based surveys were conducted with pharmaceutical companies and patient groups familiar with the SMC SIP. Semistructured interviews with representatives from HTA bodies were undertaken, along with patient group discussions with those less familiar with the SIP, to explore issues around the approach. These qualitative data informed the development of an international SIP template. Results Survey data indicated that 82 percent (18 of 22 respondents) of pharmaceutical company representatives felt that the SIP was worthwhile; 88 percent (15/17) of patient group respondents found the SIP helpful. Both groups highlighted the need for additional support and guidance around plain language summaries. Further suggestions included provision of a glossary of terms and cost-effectiveness information. Patient group interviews supported the survey findings and led to the development of a new template. HTA bodies raised potential challenges around buy-in, timing, and bias connected to the SIP approach. Conclusions The international SIP template is another approach to support deliberative processes in HTA. Although challenges remain around writing summaries for lay audiences, along with feasibility considerations for HTA bodies, the SIP approach should support more meaningful patient involvement in HTAs.
Mean–Variance Optimization for Asset Allocation

The mean–variance model is widely acknowledged as the foundation of portfolio allocation because it provides a framework for analyzing the trade-off between risk and return for gaining diversification benefits. Despite the well-known shortcomings of the model, it is often the starting point for making asset allocation decisions. In this article, the authors briefly review mean–variance optimization and approaches for resolving its limitations by demonstrating backtest results on asset allocation. Feedback from asset managers is also included to explain how optimization methods are applied in practice. TOPICS: Statistical methods, portfolio construction, performance measurement Key Findings ▪ Mean–variance optimization provides a framework for analyzing risk–return trade-offs when making asset allocation decisions. ▪ Sensitivity of the mean–variance model can be addressed with robust models, and the model generates candidate asset allocations that are informative in practice. ▪ Feedback from asset managers suggests that mean–variance optimization along with simulation and various robust methods are being applied in practice for asset allocation.
A cellular platform for the development of synthetic living machines

Amphibian embryonic explants generate motile living machines. Robot swarms have, to date, been constructed from artificial materials. Motile biological constructs have been created from muscle cells grown on precisely shaped scaffolds. However, the exploitation of emergent self-organization and functional plasticity into a self-directed living machine has remained a major challenge. We report here a method for generation of in vitro biological robots from frog (Xenopus laevis) cells. These xenobots exhibit coordinated locomotion via cilia present on their surface. These cilia arise through normal tissue patterning and do not require complicated construction methods or genomic editing, making production amenable to high-throughput projects. The biological robots arise by cellular self-organization and do not require scaffolds or microprinting; the amphibian cells are highly amenable to surgical, genetic, chemical, and optical stimulation during the self-assembly process. We show that the xenobots can navigate aqueous environments in diverse ways, heal after damage, and show emergent group behaviors. We constructed a computational model to predict useful collective behaviors that can be elicited from a xenobot swarm. In addition, we provide proof of principle for a writable molecular memory using a photoconvertible protein that can record exposure to a specific wavelength of light. Together, these results introduce a platform that can be used to study many aspects of self-assembly, swarm behavior, and synthetic bioengineering, as well as provide versatile, soft-body living machines for numerous practical applications in biomedicine and the environment.
The concept of rebalanced hemostasis in patients with liver disease: Communication from the ISTH SSC working group on hemostatic management of patients with liver disease

Patients with liver diseases acquire complex alterations in their hemostatic system that may lead to abnormalities in routine diagnostic test of hemostasis. Thrombocytopenia, prolongations in the prothrombin time and activated partial thromboplastin time, and decreased plasma fibrinogen are common in patients with advanced liver disease. Historically, liver diseases therefore have been classified as an acquired bleeding disorder. Laboratory and clinical observations have demonstrated that although routine diagnostic tests of hemostasis suggest a hypocoagulable state, patients with liver disease also tend to develop thrombotic events. Overall, patients have commensurate changes in both pro‐ and antihemostatic pathways. This new hemostatic balance, however, appears much more fragile than the hemostatic balance in individuals with normal liver function, and patients with liver disease can readily experience both hemostasis‐related bleeding and thrombotic events. These insights into the hemostatic balance in patients with liver disease have led to revised recommendations for clinical management of hemostasis. In 2020, an SSC working group within the ISTH has been founded with the aim to disseminate new concepts on prevention and treatment of bleeding and thrombosis in patients with liver disease. The current document will outline the hemostatic changes in patients with liver disease, the limitations of routine diagnostic tests of hemostasis, and the concept of rebalanced hemostasis.
Reasoning and querying bounds on differences with layered preferences

Artificial intelligence largely relies on bounds on differences (BoDs) to model binary constraints regarding different dimensions, such as time, space, costs, and calories. Recently, some approaches have extended the BoDs framework in a fuzzy, “noncrisp” direction, considering probabilities or preferences. While previous approaches have mainly aimed at providing an optimal solution to the set of constraints, we propose an innovative class of approaches in which constraint propagation algorithms aim at identifying the “space of solutions” (i.e., the minimal network) with their preferences, and query answering mechanisms are provided to explore the space of solutions as required, for example, in decision support tasks. Aiming at generality, we propose a class of approaches parametrized over user‐defined scales of qualitative preferences (e.g., Low, Medium, High, and Very High), utilizing the resume and extension operations to combine preferences, and considering different formalisms to associate preferences with BoDs. We consider both “general” preferences and a form of layered preferences that we call “pyramid” preferences. The properties of the class of approaches are also analyzed. In particular, we show that, when the resume and extension operations are defined such that they constitute a closed semiring, a more efficient constraint propagation algorithm can be used. Finally, we provide a preliminary implementation of the constraint propagation algorithms.
A fully connected deep learning approach to upper limb gesture recognition in a secure FES rehabilitation environment

Stroke is one of the leading causes of death and disability in the world. The rehabilitation of Patients' limb functions has great medical value, for example, the therapy of functional electrical stimulation (FES) systems, but suffers from effective rehabilitation evaluation. In this paper, six gestures of upper limb rehabilitation were monitored and collected using microelectromechanical systems sensors, where data stability was guaranteed using data preprocessing methods, that is, deweighting, interpolation, and feature extraction. A fully connected neural network has been proposed investigating the effects of different hidden layers, and determining its activation functions and optimizers. Experiments have depicted that a three‐hidden‐layer model with a softmax function and an adaptive gradient descent optimizer can reach an average gesture recognition rate of 97.19%. A stop mechanism has been used via recognition of dangerous gesture to ensure the safety of the system, and the lightweight cryptography has been used via hash to ensure the security of the system. Comparison to the classification models, for example, k‐nearest neighbor, logistic regression, and other random gradient descent algorithms, was conducted to verify the outperformance in recognition of upper limb gesture data. This study also provides an approach to creating health profiles based on large‐scale rehabilitation data and therefore consequent diagnosis of the effects of FES rehabilitation.
Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Evaluating startup companies is an important management process for technology business incubators and it is also a typical multicriteria decision‐making (MCDM) problem. There exist various methods that have proposed to solve MCDM problems, but these methods heavily depend on the exact criteria weight values. The decision results of these methods are unstable. Moreover, they cannot provide the improvement suggestions for the nonoptimal startup companies. To overcome these two drawbacks, we propose a novel hesitant fuzzy linguistic decision‐making method to solve the problem of evaluating startup companies. To this end, a novel semantic comparison method based on the experts' psychology and the ratio of score value to deviation degree is proposed to compare the hesitant fuzzy linguistic term sets. Then, a novel definition of hesitant fuzzy linguistic information envelopment efficiency (HFLIEE) is proposed, based on which, a novel hesitant fuzzy linguistic information envelopment analysis (HFLIEA) model and a novel preference model are proposed. By solving these models, all the alternatives can be ranked and nonoptimal alternatives can be improved. Finally, the numerical analysis is given to illustrate the applicability of the proposed models and the robustness analyses of the proposed models are provided. At the same time, they are compared with the previous hesitant fuzzy linguistic decision‐making methods.
ModPhred: an integrative toolkit for the analysis and storage of nanopore sequencing DNA and RNA modification data

Motivation DNA and RNA modifications can now be identified using Nanopore sequencing. However, we currently lack a flexible software to efficiently encode, store, analyze and visualize DNA and RNA modification data. Results Here we present ModPhred, a versatile toolkit that facilitates DNA and RNA modification analysis from nanopore sequencing reads in a user-friendly manner. ModPhred integrates probabilistic DNA and RNA modification information within the FASTQ and BAM file formats, can be used to encode multiple types of modifications simultaneously, and its output can be easily coupled to genomic track viewers, facilitating the visualization and analysis of DNA and RNA modification information in individual reads in a simple and computationally efficient manner. Availability and Implementation ModPhred is available at https://github.com/novoalab/modPhred, is implemented in Python3, and is released under an MIT license. Supplementary Data Supplementary Data are available at Bioinformatics online.