Miracle-dz/UniFAR-FTUs huggingface dataset:
Feasibility of developing hospital preparation by semisolid extrusion 3D printing: personalized amlodipine besylate chewable tablets

Abstract Semisolid extrusion (SSE) 3D printing is an emerging technology in personalized medicine. To address clinical multi-dose requirements, SSE has been explored to manufacture new preparations. In this study, amlodipine besylate (AMB) was the model drug, and SSE was the pharmaceutical strategy. We developed semisolids suitable for SSE and AMB chewable tablets with six strengths (1.5–5 mg) to meet the needs of 2–16-year-old patients. First, the semisolid extrudability was evaluated by texture analyzer, and then the amounts of carboxymethyl cellulose sodium, sodium starch glycolate, and glycerin were optimized by full factorial design. Then, rheological tests were performed to evaluate the properties of the semisolid and the effect of starch sodium glycolate on printability. Finally, the amount of corrigents was optimized using the electronic tongue. Laboratory amplified semisolids and 3D printed tablets can be stored for a few months, and the whole SSE process had no effect on crystal type. This study validated the feasibility of SSE 3D printing, and tablets with appropriate taste and cartoon appearance can meet or even exceed the traditional preparations. Our study provides a new strategy for multi-dose solid preparations and effectively meet the need for personalized amlodipine medicine. Graphical Abstract
On Some Technical Key Problems in the Development of Traction Power Supply System for High-speed Railway in China

Along with rapid development and wide application of the power electronic technology,using the experience of the German power supply mode for reference,an ideal mode of the traction power supply system is proposed,which connects with the public power grid and is relatively independent.It can solve the problems of power quality and eliminate the neutral sectioning device radically.Taking into consideration practical conditions,the cophased traction power supply scheme with the minimum compensation capacity is presented and the three-phase balance transformer is suggested to be connected with the power system so as to facilitate cophased transformation and cophased power supply through single-phase substations.The existing AT power supply modes at home and abroad are discussed and a new AT power supply mode adaptable to the situations in China is put forward.
An Optimized Fuzzy Controlled Charging System for Lithium-Ion Batteries Using a Genetic Algorithm

Fast charging is an attractive way of charging batteries; however, it may result in an undesired degradation of battery performance and lifetime because of the increase in battery temperature during fast charge. In this paper we propose a simple optimized fuzzy controller that is responsible for the regulation of the charging current of a battery charging system. The basis of the method is a simple dynamic equivalent circuit type model of the Li-ion battery that takes into account the temperature dependency of the model parameters, too. Since there is a tradeoff between the charging speed determined by the value of the charging current and the increase in temperature of the battery, the proposed fuzzy controller is applied for controlling the charging current as a function of the temperature. The controller is optimized using a genetic algorithm to ensure a jointly minimal charging time and battery temperature increase during the charging. The control method is adaptive in the sense that we use parameter estimation of an underlying dynamic battery model to adapt to the actual status of the battery after each charging. The performance and properties of the proposed optimized charging control system are evaluated using a simulation case study. The evaluation was performed in terms of the charge profiles, using the fitness values of the individuals, and in terms of the charge performance on the actual battery. The proposed method has been evaluated compared to the conventional contant current-constant voltage methods. We have found that the proposed GA-fuzzy controller gives a slightly better performance in charging time while significantly decreasing the temperature increase.
performances using cfDNA and cpDNA for detecting residual/recurrent disease in MIBC patients receiving neoadjuvant chemotherapy using an 8-gene panel (11), and for detecting TERT promoter mutations across stages and grades of incident UBC (12). Seemingly, cfDNA or cpDNA can be

The recent paper by Dudley et al. (1) entitled “Detection and surveillance of bladder cancer using urine tumor DNA” adds to the burgeoning evidence that massively-parallel sequencing of urinary DNA reliably detects tumourassociated mutations in urinary DNA. This approach promises to resolve the long overdue need for a sensitive and specific non-invasive test for bladder cancer. In this editorial we discuss the existing body of evidence and what the study by Dudley et al. contributes to this rapidlyevolving field of cancer research.
This information is current as Using Unique Molecular Identifiers Repertoires for Minor Lymphocyte Counts Quantitative Profiling of Immune

Emerging high-throughput sequencing methods for the analyses of complex structure of TCR and BCR repertoires give a powerful impulse to adaptive immunity studies. However, there are still essential technical obstacles for performing a truly quantitative analysis. Specifically, it remains challenging to obtain comprehensive information on the clonal composition of small lymphocyte populations, such as Ag-specific, functional, or tissue-resident cell subsets isolated by sorting, microdissection, or fine needle aspirates. In this study, we report a robust approach based on unique molecular identifiers that allows profiling Ag receptors for several hundred to thousand lymphocytes while preserving qualitative and quantitative information on clonal composition of the sample. We also describe several general features regarding the data analysis with unique molecular identifiers that are critical for accurate counting of starting molecules in high-throughput sequencing applications. R ecently developed high-throughput sequencing (HTS) methods for adaptive immunity studies allowed for the deep and, to a certain extent, quantitative analysis of clonotypic composition of TCR (1–4) and BCR (5–9) diversity. These methods enabled researchers to decipher the intimate architecture of immune repertoires in health and disease, both at the general scale (1–4, 10–17) and in diverse lymphocyte subpopulations, such as naive and memory T cells (10, 11, 18), functional subsets of CD4 + T cells (19, 20) or B cells (5, 8), NKT and mucosal-associated invariant T cells subsets (21–23), tumor-infiltrating lymphocytes (24, 25), tissue-specific lymphocytes (26), or Ag-specific T cells (20). Different technical approaches have been developed to prepare immune repertoire libraries that are utilizing genomic DNA (1) or RNA (3) material, commonly based on multiplex PCR or RACE methods, respectively. Upon the availability of sufficient quantity and quality of the starting material, these techniques usually perform well, albeit with some library amplification biases (e.g., unequal efficiency of V gene segment amplification in multiplex PCR) and accumulated PCR and sequencing errors that should be additionally corrected (27–30). However, there are many cases when the population of interest, such as sorted lymphocytes or lymphocytes in an available tissue sample, is represented by a limited number of cells, thus requiring a robust high-yield HTS approach that would preserve the original clonotypic composition of immune repertoire. Such approach should guarantee that 1) nearly all cells of interest are processed during sample preparation, 2) DNA or RNA material of most of those cells is preserved in the course of preliminary purification procedures, 3) DNA or RNA material of most cells …
Vehicle Rollover Avoidance by Parameter-Adaptive Reference Governor

This paper describes an approach to the vehicle rollover prevention problem that includes estimation of parameters affecting the roll dynamics and a controller accounting for uncertainties in such parameter estimation. We develop a parameter-adaptive reference governor (PARG) that modifies the driver steering input to enforce a rollover avoidance constraint, and state and input constraints. We design a recursive Bayesian estimator that produces confidence estimates of the parameters, including the center-of-gravity height. The confidence estimates inform a supervised learning algorithm, which constructs online constraint admissible sets that are lever- aged by the PARG to ensure rollover prevention. Simulation results on a Fishhook maneuver show that the method robustly prevents rollover, and that the resulting parameter estimates are contained in the confidence sets produced by the Bayesian estimator.
TRANSLATION, CULTURAL ADAPTATION AND LINGUISTIC VALIDATION OF MOTIVES FOR RISK-TAKING SCALE

Understanding motivations for high risk behaviors is an important yet neglected area in Pakistan. Although, most research on motives for risky behaviors has been done in western cultures but few studies determined its cultural diversity reflecting significant, cultural differences. To enhance the understanding of various motives for risk-taking in eastern culture, this study realized the need of a culturally valid and reliable measure to assess different motivations to engage in high risk behaviors for vulnerable population in Pakistan. This study sets out to investigate perceived motivations involved in actual risks in a sample of emerging adult destitute women (N=400) between 18-25 years approached through various shelter-homes in Pakistan. For this, a measurement scale to assess motivations to engage in high risk behaviors was translated, adapted and culturally validated. For the empirical evaluation, Exploratory Factor Analysis (EFA) performed through SPSS. 21 that reported excellent validity and reliability estimates. Moreover, it became obvious that motives to engage in risky behaviors were slightly different for Pakistani culture as compared to the existing model. All the previously explored motives reported in MRT (1. Audience Controlled, 2. Irresponsibility 3. Thrill seeking, 4. Hedonistic motivation 5. Calculated risk) were nicely emerged in the subsequent model while, few other motives also emerged in the present study which made a distinct category (Authority Defying Motives) reflecting that motivations to engage in risk-taking behaviors are somehow reliant on cultural context. All the factors showed good internal consistency ranging from α=. 70-. 82. To conclude, MRT is a valid and reliable measure for Pakistani population having strong psychometric properties, linguistic and cultural acceptability, which paves the ways for practitioners to better understand the motivations for engaging in high risk behaviors by using the available indigenous measure. ASEAN Journal of Psychiatry, Vol. 22(9), November 2021: 1-12. Keywords; Motives for Risk Taking; High Risk Behaviors; Emerging Adults; Destitute Women; Translation and Validation.
Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems

In many machine learning tasks, a common approach for dealing with large-scale data is to build a small summary, {\em e.g.,} coreset, that can efficiently represent the original input. However, real-world datasets usually contain outliers and most existing coreset construction methods are not resilient against outliers (in particular, an outlier can be located arbitrarily in the space by an adversarial attacker). In this paper, we propose a novel robust coreset method for the {\em continuous-and-bounded learning} problems (with outliers) which includes a broad range of popular optimization objectives in machine learning, {\em e.g.,} logistic regression and $ k $-means clustering. Moreover, our robust coreset can be efficiently maintained in fully-dynamic environment. To the best of our knowledge, this is the first robust and fully-dynamic coreset construction method for these optimization problems. Another highlight is that our coreset size can depend on the doubling dimension of the parameter space, rather than the VC dimension of the objective function which could be very large or even challenging to compute. Finally, we conduct the experiments on real-world datasets to evaluate the effectiveness of our proposed robust coreset method.
SimBet Semester thesis on SimBet

This thesis is about investigating the beneﬁts of adding social metrics to DTN routing on the example of a well-known social-based protocol called SimBet. We show that SimBet performs very well in synthetic scenarios, which diﬀer much from the real-traces used in the proposed implementation. By designing a model, we were able to test SimBet on several diﬀerent scenarios, in order to perform further research on SimBet’s performance on speciﬁc situations. After running several simulations, we could pinpoint to three weaknesses in the implementation, which we found to be not optimally solved. On those weaknesses, a sensitivity study has been done to see the eﬀects of the individual parameters in SimBet. Finally we show some approaches to solving them and run preliminary test, to try and ﬁnd directions for future research.
TESTING THE DIVIDEND LIFE CYCLE THEORY: EVIDENCE FROM SELECTED SUB-SAHARAN AFRICAN COUNTRIES

This paper undertakes a test of the dividend life cycle theory for quoted non-financial firms in selected Sub-Saharan African countries (Nigeria, South Africa, and Kenya). The causal and longitudinal research designs were utilized and four hundred and seventy-nine (479) nonfinancial companies in eleven (11) sub-sectors listed on Nigerian, Johannesburg, and Nairobi Stock Exchanges make up the population. However, the Utility sector was removed from the final analysis because the sample size for this subsector was not enough to carry out the system GMM analysis. Thus, the analysis was done for ten (10) subsectors. The Taro Yamani and the sample filtering technique were utilized to ascertain the size of the sample. Two hundred and thirty-nine (239) quoted nonfinancial firms were chosen and data were collected for the period 2007 to 2017. For the data analysis, the system generalized method of moments dynamic panel data regression technique was employed. This was after testing for unit root and other diagnostic tests respectively. The outcome of the empirical analysis indicates that the firms retain Earnings/Total Equity (that is, earned/contributed capital mix) has no meaningful impact on dividend pay-out while firm age has a meaningful and negative impact on dividend pay-out. Thus, the finding of this research is not in tandem with the proposition of the dividend life cycle theory. The study recommended among others that shareholders must consider other means of sustaining dividends for firms since mere age will not guarantee dividend pay-out.
Perceived Stress and its Contributing Factors among a Group of Egyptian Women during COVID-19 Lockdown

Background: The pandemic of corona virus disease [COVID]-19 had its great impacts on global health due to the increasing both morbidity and mortality. In addition, being quarantined is linked with high stress levels, insomnia, irritability and trauma-related disorders particularly in vulnerable populations. Therefore, there is a need to assess accurately and timely the magnitude of psychological health outcomes in those having exposure to COVID-19 pandemic. The Aim: The current work aimed to assess the perceived stress level among a group of Egyptian women and to explore the potential contributing factors for that during the COVID-19 lockdown. Methods: A cross-sectional survey targeted educated women from different Egyptian governorates, and of different socioeconomic standards. The total sample was 286 women who were recruited by non-probability snowball sampling and through a semi-structured, online questionnaire comprising socio-demographic data, the validated Arabic version of Cohen Perceived Stress Scale 10 [PSS]. Possible contributing factors of the perceived stress due to COVID-19 were also inquired. Results: total females who responded to the questionnaire were 286 with mean age of 46.5± 11.0 years. During the quarantine period, the total score of the perceived stress scale was 17.1±5.37, and both high and moderate levels of stress were recorded among 73.4% of the studied sample. Stress level was significantly influenced by disruptions of social communication with friends and families, "getting basic needs for health and safety are unmet then ", conflicts between mother and her children represented as a load", being younger women [below 50 years], and "feel stressed due to inability for social gatherings". Conclusion: COVID -19 pandemic has its obvious psychological impact on females, and many factors were contributing to such situation, which put the spotlight on the importance of taking these impacts into consideration when designing policies to slow the spread of the pandemic.
Study of consensus protocols and improvement of the Delegated Byzantine Fault Tolerance (DBFT) algorithm

Nowadays, blockchain is one of the most popular and innovate technologies over the world. Although this technology appears for first time in the Bitcoin cryptocurrency, in recent years, a lot of researchers and industries from different fields such as banking, financial, supply chain management, etc. have given more involved than ever before. The blockchain is implemented in decentralized and distributed ledgers in peer-to-peer (p2p) networks where non-trusting peers can implement digital asset transactions without the need of central authority. Then, other peers in the network, according specific rules determined by the network, validate these transactions, insert them in the block and append the block in the chain (ledger). The key contribution for the proper operation of the blockchain is the consensus protocols. Through these protocols, all the peers in the network or the majority of them, they have to reach an agreement for a specific block in order to insert it in the chain based on different blockchains rules. In this master thesis, we will analyze in depth the general architecture of the blockchain and various consensus protocols that implemented in different blockchains in order to be able to improve the Delegated Byzantine Fault Tolerance (DBFT) consensus algorithm, which is used in the NEO blockchain technology. Finally, a development of a reputation mechanism is needed based on the improvement of the DBFT algorithm in order to measure the reputation of the peers for a specific day.
(Online: 2090-2549) MORPHOLOGICAL DESCRIPTION OF COSMOCERCA VRCIBRADICI (COSMOCERCIDAE RAILLIET, 1916) AND PHYSALOPTERA BAINAE (PHYSALOPTERIDAE, LEIPER 1908) IN CHALCIDES OCELLATUS FROM EGYPT: A LIGHT AND SCANNING ELECTRON MICROSCOPIC STUDY

Cosmocerca vrcibradici (Cosmocercidae) and Physaloptera bainae (Physalopteridae) are two intestinal nematodes obtained from a scincid lizard, Chalcides ocellatus (Scincidae). The study gave the first morphological description of C. vrcibradici and P. bainae using light and scanning electron microscopy. A cosmocercid nematode C. vrcibradici assigned to genus Cosmocera, possessing small mouth surrounded by three lips provided with four sub-median cephalic papillae and each one has a pair of lateral amphids. Male was 2.4-2.7 (2.6±0.1) mm long; maximum width 0.2-0.23 (0.21±0.01) can be easily distinguished from its congeners by the presence of lateral alae and small well sclerotized gubernaculum and ended conically with a tapered tail. Females measured 1.9 3.7 (2.8±0.1) mm in length & 0.24 0.42 (0.38±0.01) mm in width ended with a tapered tail. Besides, all recovered females were gravid filled with large number of embryonated eggs. Physaloptera bainae assigned to genus Physaloptera characterized by long robust body measured 3.21-5.47 (4.35±0.10) long and 0.58-0.65 (0.62±0.01) in maximum width, oral openings with two semicircular pseudolabia, cuticle dilatation at anterior ed tail. Only recovered parasites were females with didelphic uterus the main characteristics feature among between species. These observations have allowed a more detailed description of both nematode taxonomy and classification.
Overview of the Recent Progress of Suppressing the Dendritic Growth on Lithium Metal Anode for Rechargeable Batteries

The lithium metal has been considered as a competitive material for anode on the high-energy storage battery because of its various advantages, such as high capacity, low density, and the lowest electrochemical potential. However, the uncontrolled dendritic growth on the anode surface could cause the short circuit, even explosion of the battery. Therefore, strategies about how to effectively inhibit the formation of dendrites is of great importance. This paper will first give a brief introduction on the growth of dendrites. The attention is then focused on the recent advancements to suppress the dendrite growth of lithium metal, such as the optimization of electrolyte, application of artificial solid electrolyte interphase (SEI), and the modification of lithium anode. The future research directions will be presented at the end.
Performance analysis of texture characterization techniques for lung nodule classification

Lung cancer ranks very high on a global index for cancer-related casualties. With early detection of lung cancer, the rate of survival increases to 80-90%. The standard method for diagnosing lung cancer from Computed Tomography (CT) scans is by manual annotation and detection of the cancerous regions, which is a tedious task for radiologists. This paper proposes a machine learning approach for multi-class classification of the lung nodules into solid, semi-solid, and Ground Glass Object texture classes. We employ feature extraction techniques, such as gray-level co-occurrence matrix, Gabor filters, and local binary pattern, and validate the performance on the LNDb dataset. The best performing classifier displays an accuracy of 94% and an F1-score of 0.92. The proposed approach was compared with related work using the same dataset. The results are promising, and the proposed method can be used to diagnose lung cancer accurately.
Verification Analysis of the Relationship Between Soil Pressure and Displacement of Retaining Structure

Variation laws of earth pressure accounting for the displacement of are taining wall can be well described by mathmatical fitting in the study of the relationship between earth pressure and retaining wall displacement. The common mathematical function expressions of earth pressure displacement of retaining wall can be divided into sinusoidal function model, exponential like function model, hyperbolic function model, fitting function and semi-numerical and semi-analytical model function, etc. The characteristics and shortcomings of the current expression of earth pressure displacement function are summarized. Then combined with the field test and model test, the applicability and characteristics of various mathematical functions in predicting the displacement of earth pressure with retaining structures are analyzed. The results show that when the displacement is small, the sinusoidal function model and the quasi-exponential function model are close to the measured results. When the displacement of retaining structure is large, the fitting results of hyperbolic model and semi-numerical and semi-analytical model are better. For the prediction of earth pressure displacement relationship in passive area, the buried depth has a great influence. And the error between the theoretical value and the actual value has a great influence on the fitting result of the model.