Miracle-dz/UniFAR-FTUs huggingface dataset:
Chromatographic considerations in the standardization of liquid chromatographic methods used for extractables screening

ABSTRACT Organic extractables and leachables (E&L) from drug product packaging, manufacturing components, and delivery devices are of concern as they could impact product quality and/or user safety. Proper E&L assessment involves chromatographic profiling of a drug product or extraction solvent, including liquid chromatography with UV absorption and mass spectrometric detection (LC/UV/MS), to uncover these substances and establish their identities and concentrations. Relative retention time (RRT) could be used as one parameter for identifying E&L and relative response factors (RRFs) could be used for quantifying extractables if (a) RRT and RRFs were consistent across various LC/UV/MS methods and instrument systems used for profiling and (b) a database existed for RRT and RRFs. This manuscript addresses (a) by examining the variation in RRT and RRF for model extractables across variations to a specified LC/UV/MS method. Creating and populating a database of relative retention and response data (b) is beyond the manuscript’s scope. Studies which examined small, and more controlled, variations to the method and larger, and less controlled, variations were performed. These assessments support the conclusions that if the operational parameters of the LC/UV/MS are specified and if only relatively minor deviations from these parameters are allowed, then RRTs are sufficiently reproducible that they are an effective means of securing tentative extractable’s identities and UV RRFs are sufficiently reproducible that they provide accurate extractable’s concentrations. MS RRFs are less reproducible and only estimate concentration. GRAPHICAL ABSTRACT
Evaluating convection-permitting ensemble forecasts of precipitation over Southeast Asia

Forecasting rainfall in the tropics is a major challenge for numerical weather prediction. Convection-permitting (CP) models are intended to enable forecasts of high-impact weather events. Development and operation of these models in the tropics has only just been realised. This study describes and evaluates a suite of recently developed Met Office Unified Model CP ensemble forecasts over three domains in Southeast Asia, covering Malaysia, Indonesia and the Philippines.Fractions Skill Score is used to assess the spatial scale-dependence of skill in forecasts of precipitation during October 2018 - March 2019. CP forecasts are skilful for 3-hour precipitation accumulations at spatial scales greater than 200 km in all domains during the first day of forecasts. Skill decreases with lead time but varies depending on time of day over Malaysia and Indonesia, due to the importance of the diurnal cycle in driving rainfall in those regions. Skill is largest during daytime when precipitation is over land and is constrained by orography. Comparison of CP ensembles using 2.2, 4.5 and 8.8 km grid spacing and an 8.8km ensemble with parameterised convection reveals that varying resolution has much less effect on ensemble skill and spread than the representation of convection. The parameterised ensemble is less skilful than CP ensembles over Malaysia and Indonesia and more skilful over the Philippines; however, the parameterised ensemble has large drops in skill and spread related to deficiencies in its diurnal cycle representation. All ensembles are under-spread indicating that future model development should focus on this issue.
Préparation et caractérisation d'extraits d'Argania spinosa et d'huile d'argan et évaluation de leurs effets neuroprotecteurs in vivo et in vitro

Parmi les huiles naturelles, l'huile d'argan suscite beaucoup d’interet. Elle a ete utilisee en medecine traditionnelle, en usage externe par les femmes berberes pour les soins corporels et capillaires, et en usage interne pour prevenir certaines maladies cardiovasculaires. L’huile d’argan se caracterise par ses fonctions hypocholesterolemiantes, anti-diabetique et antiproliferative sur des lignees cancereuses humaines de prostate. Riche en acides gras insatures, l’huile d’argan est caracterisee egalement par ses composes mineurs : polyphenols, tocopherols et sterols qui lui conferent des proprietes antioxydantes. Le role des antioxydants alimentaires dans la fonction neurologique et dans certaines maladies lies a l’âge est centree sur la vitamine E qui est une molecule majoritaire de l’huile d’argan dotee. L’objectif de ce travail a consiste dans un premier temps en une etude phytochimique et en une evalutation du pouvoir antioxydant des extraits d’arganier de deux regions marocaines. Une caracterisation biochimique de la composition de l’huile d’argan a aussi ete realisee. Dans un second temps, une evaluation des effets protecteurs de l’huile d’argan ou certains de ces composes majoritaires a ete realisee in vitro sur des oligodendrocytes murins 158N et in vivo sur des rats. ces effets ont ete specifies dans un environnement pro-oxydant et cytotoxique mime par le 7-cetocholesterol (7KC) et l’AlCl3. La cytotoxicite du 7KC induit divers effets au niveau de la mitochondrie (modification fonctionnelle), ce qui conduit a une rupture de l’equilibre RedOx (surproduction d’especes radicalaires de l’oxygene), a une induction d’apoptose et d’autophagie, a une perte d’adhesion, a une diminution de la proliferation et a des dysfonctions du lysosome. Le 7KC affecte aussi l’expression des marqueurs peroxysomaux (ABCD1, ABCD2, ACOX1) ainsi que l’expression de facteur de transcription PPARα au niveau cellulaire. L’etude in vivo realisee sur des rats Wistar traites a 100 mg/kg d’AlCl3, a montre qu’AlCl3 induit une rupture de l’equilibre RedOx en diminuant les activites des enzymes anti-oxydantes (catalase, superoxyde dismutase, les glutathions) au niveau du cortex, une alteration des fonctions cognitives qui ont ete etroitement liees aux maladies neurodegeneratives, et des modifications des parametres plasmatiques. AlCl3 induit une legere perte du poids corporel des rats tout au long de la periode de traitement. Dans son ensemble, le travail realise montre que l’huile d’argan est capable de s’opposer au stress oxydatif induit par 7KC et AlCl3. L’huile d’argan pourrait etre potentiellement etre interessante pour traiter les maladies neurodegeneratives. Elle pourrait exercer des effets cytoprotecteurs et antioxydants ce qui permet d’envisager de nouveaux domaines d’applications pour cette huile.
Plasma polymerization of poly(3,4-ethylenedioxyethene) films: The influence of plasma gas phase chemistry

Poly(3,4-ethylenedioxythiophene) (PEDOT) is a conducting polymer and so has many technological applications. Plasma polymerization is an attractive technique by which to form PEDOT because it does not require solvents and can be performed at low substrate temperatures. However to date, plasma polymerized PEDOT have electrical conductivities that are at least 4 orders of magnitude lower than PEDOT synthesized using other methods. In this paper, the authors investigate the influence of the plasma gas phase chemistry on the conductivity of plasma polymerized films using infrared spectroscopy and complementary density functional theory calculations. The authors show that the monomer of PEDOT, 3,4-ethylenedioxythiophene (EDOT), begins to decompose at very low energies per molecule (<1 eV/n) with its weakest bonds, the C–O bonds of the dioxy ring, breaking first. Little, or no, fragmentation of the aromatic (thiophene) ring is observed. Since reactions can now occur at the 3,4-positions of the thiophene ring as.
Privacy Preserving Load Control of Residential Microgrid via Deep Reinforcement Learning

Demand side management has been proved to be effective in improving the operating efficiency of microgrids, while posing a severe threat to user privacy. This paper proposes a novel privacy preserving load control scheme for the residential microgrid, in which the microgrid operator manages a multitude of home appliances including electric vehicles (EVs) and air conditioners (ACs). This problem is formulated as a partially observable Markov decision process, since users’ privacy information including indoor temperatures associated with ACs and arrival/departure times of EVs cannot be observed by microgrid operator. To address the formulated problem with high-dimensional continuous action space caused by massive controllable appliances, we develop a novel deep reinforcement learning algorithm by introducing credit assignment mechanism. Moreover, we integrate recurrent neural network to accommodate the partial observability of state due to privacy issues. Simulation results demonstrate the superiority and flexibility of the developed algorithm and verify the advantages of the proposed scheme compared with prior privacy preserving load control method.
Separation of 2-naphthol atropisomers on cyclofructan-based chiral stationary phases

ABSTRACT A set of fifteen 2-naphthol-derived atropisomers were evaluated on three different cyclofructan-based chiral stationary phases (CSP). The cyclofructan CSPs were a dimethylphenyl-derivatized cyclofructan 7 (CF7-DMP), a isopropyl (CF6-P) and a R-naphthylethyl cyclofructan 6 (CF6-RN) derivative, all bonded to 5-µm spherical fully porous silica particles packed into three 25 cm × 4.6 mm columns (commercially available as Larihc columns). The 15 atropisomers were analyzed in the normal-phase mode with heptane/alcohol mobile phases. The CF7-DMP column was the most effective partially or fully separating 14 of the 15 compounds (93%). All 15 compounds could be separated by at least one cyclofructan column. Five compounds could be partially or fully separated by all three CSPs. The effect of ethanol, 2-propanol and butanol as 5 and 10% v/v polar modifiers in heptane was studied. A prototype 15 cm × 4.6 mm column packed with superficially porous 2.7 µm CF6-P bonded particles was tested with the same set of compounds and a standard HPLC system. The increased efficiency and solvent saving were significant. GRAPHICAL ABSTRACT
A comparative study of transferable theoretical aspherical pseudoatom data bank and classical force field in predicting the electrostatic interaction in molecular dimers

Accurate and fast evaluation of electrostatic interactions in molecular systems is one of the most challenging tasks in the rapidly advancing field of macromolecular chemistry, including molecular recognition, protein modeling and drug design. Electrostatic interactions are extremely essen tial in biological system and it is also well known that ab-initio calculations are very expensive and time consuming. In this study we have evaluated electrostatic interaction energy of S66 (1) and JSCH-2005(2) data sets, total 203 molecular complexes. These complexes are representa tive of a range of chemical and biological systems for which hydrogen bonding, electrostatic, π stacking and van der waals interactions play important role. Reference benchmark energies were obtained directly from wavefunctions at the level of theory (DFT/B3LYP/aug-cc-pVTZ)(3; 4) using SAPT: Symmetry-Adapted Perturbation Theory (5). Electrostatic energy calculated on the basis of UBDB databank(6)-Exact Potential Multipole Method(EPMM)(7) of aspherical models and force fileds were compared with corresponding reference results. Root mean square error’s (RSMEs) and regression coe∥cient’s were used as a quantitative measure of the quality of the analyzed properties. The energy trends are well consistent ( R2 ≈ 0.98) for the UBDBEPMM method as compared to AMBER(8) and CHARMM force field methods (9)( R2 ≈ 0.95). RSMEs are about 1-3 and 8-15 Kcal mol−1 for the UBDB and force field methods, respectively. This study shows that estimation of electrostatic interaction energy using UBDB databank is more accurate and fast when compared to other known methods and open new possibility of applying on macromolecules.
Comparative study of the relationship between childhood traumas with personality function and pathological traits in patients with borderline personality disorder and non-patient group

Introduction: A review of the background of people with borderline personality disorder shows that most of these people were raised in shaky family environments. Aim: The aim of this study was to predict the relationship between personality function and pathological traits in patients with borderline personality disorder and normal group through childhood traumas. Method: The present study was a causal-comparative and correlational study. The statistical population consisted of 214 students of the academic year 2018-2019 of Kurdistan University and 25 patients with borderline personality disorder hospitalized from December to February 2018 in Ghods Psychiatric Hospital, by available sampling method. And Childhood Injury Questionnaires (Bernstein and Fink, 1998), the Large-Scale Personality Function Levels (Murray et al., 2011), the Long Version of the Personality Checklist for the Fifth Edition of the Diagnostic and Statistical Manual of Psychiatric Disorders (American Psychiatric Association, 2013) and the Personality Disorders Questionnaire (First et al., 1997) responded. Data analysis was performed using Pearson correlation test and logistic regression analysis. Results: There was a direct and significant relationship between the scores of borderline personality disorder and personality function at the level of (P<0.000) and childhood trauma at the level of (P<0.000). The findings of the present study using logistic regression showed that personality dysfunction and childhood traumas at the (P<0.000) level are able to distinguish between 23 and 48% of the group with borderline personality disorder from the non-clinical group. Conclusion: According to the results of borderline personality disorder, personality trauma can be predicted through childhood traumatic experiences and dysfunction. Clinicians are advised to consider the role of childhood trauma in dealing with borderline patients.
An RF-Based Positioning Method for Tracing a Cluster of Moving Scatterers in Non-Stationary Indoor Environments

This letter presents a novel iterative positioning method for tracing the body segments of a person moving indoors using radio-frequency (RF) signals. The indoor space is equipped with a multiple-input multiple-output (MIMO) communication system. The person is modelled by a cluster of moving point scatterers, playing the role of moving body segments. The proposed technique estimates the time-variant (TV) positions of the moving scatterers by fitting the TV channel transfer function (TVCTF) of the channel model as close as possible to the TVCTF of the measured channels. Numerical results are presented to demonstrate the accuracy of this method.
Ecological Efficiency Analysis in Zhejiang Province: Based on Improved Super-SBM Model

This paper use the super efficiency SBM-DEA model with undesirable outputs to calculate the ecological efficiency of Zhejiang Province from 2001 to 2018, and construct multiple linear regression model that evaluating the influencing factors of ecological efficiency based on it. The ecological efficiency of Zhejiang Province fluctuated and increased during the study period, which was mainly driven by pure technical efficiency. In the multiple regression analysis, it can be concluded that income factors, structural factors and institutional factors have a gradually weakening positive impact on ecological efficiency. This paper argues that Zhejiang Province should make full use of regional advantages, resource advantages and talent advantages on the basis of maintaining the current industrial level. It is advised to vigorously develop high-tech industries, strengthen international communications on knowledge and seek new economic growth points. Finally a higher level of coordination between economic development and ecological protection can be achieved.
Effect of surfactants, pH and water hardness on the surface properties and agglomeration behavior of engineered TiO2 nanoparticles

The influence of sodium dodecyl sulfate (SDS) on the stability of TiO2 engineered nanoparticle (ENP) dispersions is investigated under various pH conditions, SDS and divalent cation concentrations. Based on different scenarios and systematic measurements of surface charges and z-average sizes, a detailed mechanistic approach is proposed assuming surfactant adsorption/desorption, charge inversion, cation bridging, specific adsorption, hydrophobic effects, agglomeration and disagglomeration. Adsorption of SDS on oppositely charged TiO2 nanoparticles is found to strongly modify their stability. Formation of large agglomerates can be achieved via several routes: i) in the absence of SDS and by adjusting the pH close to the TiO2 point of zero charge, and ii) in the presence of SDS at a concentration where the positive surface charges of the TiO2 nanoparticles are counterbalanced by the SDS negative charges (charge neutralization). It is also found that hydrophobic interaction mechanisms between the SDS molecules can also promote the formation of large structures. The influence of pH variations on TiO2–SDS electrostatic complexes, formed at low pH, indicates that an excess of SDS is required to prevent the formation of large agglomerates upon pH changes. At low or intermediate SDS concentrations, TiO2 stability is governed by the subtle interplay of SDS adsorption and TiO2 surface charge acid–base properties. The presence of divalent electrolytes (water hardness) is found to reduce the SDS amount adsorbed on TiO2 ENPs and to promote the formation of large micron-sized agglomerates by cation bridging. Our results also indicate that the dispersion preparation protocol is an important issue to consider when ENPs and SDS mixtures have to be prepared and that for the formation of “individually” coated and stable nanoparticles, punctual addition of SDS is required at concentrations higher than the isoelectric point.
Effect of dietary incorporation of Sahjan (Moringa oleifera) and Tej Patta (Cinnamomum tamala) leaf powder as feed additive on haemato-biochemical parameters in commercial broiler chickens

A feeding trial was conducted to discern the effect of dietary incorporation of sahjan (Moringa oleifera) leaf powder and tejpatta (Cinnamomum tamala) powder on haemato-biochemical parameters in commercial broiler chickens. 120, day-old broiler chicks were divided randomly into 4 treatment groups with 3 replicate each i.e. 10 broiler chicks per replicate. The feeding trail lasted for 42 days and blood samples were collected at the end of feeding trial. Chicks of treatment T1 (control) were fed basal diet (starter and finisher diet), whereas in treatment groups T2, T3 and T4, basal diet was incorporated with 0.5% sahjan leaf powder, 0.5% tejpatta powder and 0.25% sahjan leaf powder with 0.25% tejpatta powder, respectively. There was no significant difference was observed in haematological parameters among different treatment groups. The average haemoglobin content of different groups T1, T2, T3 and T4 was 9.06, 9.26, 9.30 and 9.28 gram per cent, respectively. Maximum serum cholesterol reduction was observed in the group T4 (135.35 mg/dl) which was significantly different from other incorporated groups T1, T2, T3 (147.98, 141.92 and 142.42 mg/dl). The serum triglycerides concentration in broiler chickens reduced significantly in T4 (57.62 mg/dl), T3 (59.15 mg/dl), T2 (60.02 mg/dl) of broiler chicks fed diets included with sahjan and tejpatta alone and their combination as compared to T1 (62.28 mg/dl). There was no significant difference in serum total protein, albumin, globulin and glucose concentrations as well as serum ALP, ALT and AST activities among the different treatment groups. Therefore, it could be concluded that incorporation of sahjan (Moringa oleifera) leaf powder and tejpatta (Cinnamomum tamala) powder in the diets of commercial broiler chickens had lower level of serum cholesterol and triglyceride.
Using Word Embeddings in Turkish Part of Speech Tagging

The close relation between the stem (relatively the word meaning) and part of speech tag of the word turns part of speech tagging as an important preprocessing task in natural language processing and understanding problem. For example, if the Turkish word “gelecek” is labeled as noun, the word stem is to be “gelecek” meaning future. If it is labeled as verb, the stem is “gel” and in English it means, “come”. In many languages including Turkish, part of speech tagging problem is generally solved by rule based approaches. In this paper, a setup where the neural network architecture SENNA together with word embeddings is employed. The combination of Wikipedia 2016 and METU corpora is utilized in training of word embeddings; PARDER is used in part of speech training and testing. The word embeddings that are obtained by different methods and different vector sizes are evaluated intrinsically considering analogic and semantic similarity distances; and assessed extrinsically based on the performance on part of speech tagging task.
Perturbation-Seeking Generative Adversarial Networks: A Defense Framework for Remote Sensing Image Scene Classification

The methods for remote sensing image (RSI) scene classification based on deep convolutional neural networks (DCNNs) have achieved prominent success. However, confronted with adversarial examples obtained by adding imperceptible perturbations to clean images, the great vulnerability of DCNNs makes it worth exploring effective defense methods. To date, numerous countermeasures for adversarial examples have been proposed, but how to improve the defensive ability for unknown attacks still to be answered. To address this issue, in this article, we propose an effective defense framework specified for RSI scene classification, named perturbation-seeking generative adversarial networks (PSGANs). In brief, a new training framework is designed to train the classifier by introducing the examples generated during the image reconstruction process, in addition to clean examples and adversarial ones. These generated examples can be random kinds of unknown attacks during training and thus are utilized to eliminate the blind spots of a classifier. To assist the proposed training framework, a reconstruction method is developed. First, instead of modeling the distribution of clean examples, we model the distributions of the perturbations added in adversarial examples. Second, to make a tradeoff between the diversity of the reconstructed examples and the optimization of PSGAN, a scale factor named seeking radius is introduced to scale the generated perturbations before they are subtracted by the given adversarial examples. Comprehensive and extensive experimental results on three widely used benchmarks for RSI scene classification demonstrate the great effectiveness of PSGAN when faced with both known and unknown attacks. Our source code is available at https://github.com/xuxiangsun/PSGAN.
Effects of preheating on ice growth in antifreeze polypeptides solutions in a narrow space

We conducted measurements on the unidirectional freezing of aqueous solutions of polypeptide or of winter flounder antifreeze protein. The polypeptide was based on a part of the antifreeze protein. We measured temperatures in the solutions and ice with a small thermocouple, and defined the interface temperature as the temperature at the tip of the serrated or pectinate interface. It was found that the interface temperature of these solutions was lower than that of pure water. To vary the activity of these solutes, we preheated the solutions and cooled them before conducting the measurements. We found that preheating for several hours caused further decreases in the interface temperature and a decrease in the interface velocity. In addition, the inclined interfaces became wider as a result of the preheating. Thus, the supercooled states in the solutions were enhanced by the preheating. To investigate the reasons for these changes, we measured the aggregates of the solutes in the solutions. These aggregates became larger as a result of preheating. It can therefore be concluded that these large aggregates attenuated the ice growth by their interaction with the ice surfaces.