Miracle-dz/UniFAR-FTUs huggingface dataset:
A Method to Measure Dynamic Capabilities though Resource Integration

Dynamic capabilities (DC) have been suggested as a key organisational characteristic for innovation and competitive advantage. Although a strongly emergent theoretical approach in strategy and organisation research few attempts have been made to make this concept operational. In this paper we outline a novel approach to measure DC as the degree of how the resources of a firm are integrated over time. We illustrate using a case study example and examine how hierarchical cluster analysis can provide measures of resource integration that can be used to model dynamic capabilities.
Early Sowing of Quinoa Cultivars, Benefits from Rainy Season and Enhances Quinoa Development, Growth, and Yield under Arid Condition in Morocco

Quinoa is a highly nutritious and gluten-free crop. It is a good alternative crop to cereals in the context of climate change. In the process of introducing quinoa to an arid region of Morocco (Rehamna), late sowing results in stunted plants and low yields due to insufficient precipitations and high temperatures around the flowering stage. Early sowing of short-cycle cultivars constitutes a good strategy to enhance growth and yields. A field experiment was conducted in the Rehamna region in 2020–2021 to investigate the effect of the sowing date on quinoa growth, development, and yield. Two cultivars, ICBA-Q5 and Titicaca, and five sowing dates from 15 November to 15 March were evaluated. Results showed that December sowing enhanced plant height, total leaf area, the number and dry weight of branches, leaves, and panicles, and enhanced quinoa productivity, due to high precipitations, optimal temperatures, and a short photoperiod. The highest grain yield (0.84 t ha−1) was obtained with ICBA-Q5. Late sowing decreased the yield and growth and reduced the number of days to panicle emergence, flowering, and maturity for both cultivars. Early sowing of ICBA-Q5 is recommended to increase quinoa yield in arid regions of Morocco.
Measuring the effectiveness of extrapolation techniques associated with the multigrid method applied to the Navier-Stokes equations

In this work, we applied different extrapolation techniques in association with the multigrid method to discover which one is the most effective in reducing the iteration error and the processing time (CPU time), as well as in improving the convergence factors. The mathematical model studied refers to the two-dimensional laminar flow of an isothermal time-dependent incompressible fluid modeled by the Navier-Stokes equations, with , solved iteratively with the projection method and the Finite Volume Method. The extrapolation methods used were: Aitken, Empiric, Mitin, scalar Epsilon, scalar Rho, topological Epsilon, and topological Rho. A two-step application was performed: first, extrapolators methods were applied individually after the use of the multigrid method. Then, the best-performing extrapolation techniques were used in the second step, where they were applied between the cycles of the multigrid method. The methods that presented the best convergence properties in the first stage were topological and scalar Epsilon. In the second stage, both methods maintained their performance, however, the topological Epsilon method presented more significant convergence rates than the scalar Epsilon. The other parameters analyzed were: the storage memory peak, the dimensionless norm of the residual based on the initial estimate, and the error norms of iteration. Thus, it was possible to state which extrapolation technique performed best and to compare it with the multigrid method with no extrapolation, which in this study was the topological Epsilon method.
Inverse ISAsomes in Bio-Compatible Oils—Exploring Formulations in Squalane, Triolein and Olive Oil

In contrast to their more common counterparts in aqueous solutions, inverse ISAsomes (internally self-assembled somes/particles) are formulated as kinetically stabilised dispersions of hydrophilic, lyotropic liquid-crystalline (LC) phases in non-polar oils. This contribution reports on their formation in bio-compatible oils. We found that it is possible to create inverse hexosomes, inverse micellar cubosomes (Fd3m) and an inverse emulsified microemulsion (EME) in excess squalane with a polyethylene glycol alkyl ether as the primary surfactant forming the LC phase and to stabilise them with hydrophobised silica nanoparticles. Furthermore, an emulsified L1-phase and inverse hexosomes were formed in excess triolein with the triblock-copolymer Pluronic® P94 as the primary surfactant. Stabilisation was achieved with a molecular stabiliser of type polyethylene glycol (PEG)-dipolyhydroxystearate. For the inverse hexosomes in triolein, the possibility of a formulation without any additional stabiliser was explored. It was found that a sufficiently strong stabilisation effect was created by the primary surfactant alone. Finally, triolein was replaced with olive oil which also led to the successful formation of inverse hexosomes. As far as we know, there exists no previous contribution about inverse ISAsomes in complex oils such as triolein or plant oils, and the existence of stabiliser-free (i.e., self-stabilising) inverse hexosomes has also not been reported until now.
Identifying novel phenotypes of elevated left ventricular end diastolic pressure using hierarchical clustering of features derived from electromechanical waveform data

Introduction Elevated left ventricular end diastolic pressure (LVEDP) is a consequence of compromised left ventricular compliance and an important measure of myocardial dysfunction. An algorithm was developed to predict elevated LVEDP utilizing electro-mechanical (EM) waveform features. We examined the hierarchical clustering of selected features developed from these EM waveforms in order to identify important patient subgroups and assess their possible prognostic significance. Materials and methods Patients presenting with cardiovascular symptoms (N = 396) underwent EM data collection and direct LVEDP measurement by left heart catheterization. LVEDP was classified as non-elevated ( ≤ 12 mmHg) or elevated (≥25 mmHg). The 30 most contributive features to the algorithm output were extracted from EM data and input to an unsupervised hierarchical clustering algorithm. The resultant dendrogram was divided into five clusters, and patient metadata overlaid. Results The cluster with highest LVEDP (cluster 1) was most dissimilar from the lowest LVEDP cluster (cluster 5) in both clustering and with respect to clinical characteristics. In contrast to the cluster demonstrating the highest percentage of elevated LVEDP patients, the lowest was predominantly non-elevated LVEDP, younger, lower BMI, and males with a higher rate of significant coronary artery disease (CAD). The next adjacent cluster (cluster 2) to that of the highest LVEDP (cluster 1) had the second lowest LVEDP of all clusters. Cluster 2 differed from Cluster 1 primarily based on features extracted from the electrical data, and those that quantified predictability and variability of the signal. There was a low predictability and high variability in the highest LVEDP cluster 1, and the opposite in adjacent cluster 2. Conclusion This analysis identified subgroups of patients with varying degrees of LVEDP elevation based on waveform features. An approach to stratify movement between clusters and possible progression of myocardial dysfunction may include changes in features that differentiate clusters; specifically, reductions in electrical signal predictability and increases in variability. Identification of phenotypes of myocardial dysfunction evidenced by elevated LVEDP and knowledge of factors promoting transition to clusters with higher levels of left ventricular filling pressures could permit early risk stratification and improve patient selection for novel therapeutic interventions.
An automatic learning rate decay strategy for stochastic gradient descent optimization methods in neural networks

Stochastic Gradient Descent (SGD) series optimization methods play the vital role in training neural networks, attracting growing attention in science and engineering fields of the intelligent system. The choice of learning rates affects the convergence rate of SGD series optimization methods. Currently, learning rate adjustment strategies mainly face the following problems: (1) The traditional learning rate decay method mainly adopts manual manner during training iterations, the small learning rate produced from which causes slow convergence in training neural networks. (2) Adaptive method (e.g., Adam) has poor generalization performance. To alleviate the above issues, we propose a novel automatic learning rate decay strategy for SGD optimization methods in neural networks. On the basis of the observation that the convergence rate's upper bound enjoys minimization in a specific iteration concerning the current learning rate, we first present the expression of the current learning rate determined by historical learning rates. And merely one extra parameter is initialized to generate automatic decreasing learning rates during the training process. Our proposed approach is applied to SGD and Momentum SGD optimization algorithms, and concrete theoretical proof explains its convergence. Numerical simulations are conducted on the MNIST and Cifar‐10 data sets with different neural networks. Experimental results show that our algorithm outperforms existing classical ones, achieving faster convergence rate, better stability, and generalization performance in neural network training. It also lays a foundation for large‐scale parallel search of initial parameters in intelligent systems.
Determination of Heavy Metals in Tobacco Leaves and Their Growing Soils in Assosa District, Benshangul Gumuz Regional State, Ethiopia

Tobacco is a commercial plant that can accumulate heavy metals in its leaves. In this study, we investigated the levels of selected heavy metals (Mn, Cu, Zn, Cd, and Pb) in tobacco leaves and their growing soils from Assosa District, Benshangul Gumuz Regional State, Ethiopia. Both samples were collected from five tobacco farmlands. The samples were digested before quantitative determinations of the metals via inductively coupled plasma optical emission spectroscopy (ICP-OES). Repeatability and recovery studies were used to evaluate the efficiency of the method. Repeatability was evaluated by analyzing replicate samples and expressed as relative standard deviations (RSD) were below 10.0. Recovery or percent recovery (%R) studies, which were performed by spiking known concentrations of metals into the samples, ranged from 85.67 111.33% and 84.25 114.00% for tobacco leaves and soil samples, respectively, indicating that the employed method is valid for the analysis of the metals. The concentrations of metals in tobacco leaf samples were: 0.75 -1.18 mg/kg, Mn; 0.11-0.21 mg/kg, Cu; 0.58-1.16 mg/kg, Zn; and not quantified (NQ) 0.01 mg/kg, Cd. In soil samples, their concentrations were: 1.59-8.04 mg/kg, Mn; 0.32 0.38 mg/kg, Cu; and 0.29 1.26 mg/kg, Zn; and 0.17 0.31 mg/kg, Pb. Except in one tobacco leaf sample, Pb was below the limit of quantification (LOQ). Similarly, in all soil samples, the concentration of Cd was below LOQ. The findings indicate that the concentrations of the studied heavy metals in both tobacco leaves and soil samples are below their WHO permissible limits in soil and plants. However, the levels of Zn in Amba and Basha tobacco leaves were higher than the WHO permissible limit in plants.
In Vitro and In Vivo Studies for the Investigation of γ-Globin Gene Induction by Adhatoda vasica: A Pre-Clinical Study of HbF Inducers for β-Thalassemia

Fetal hemoglobin (HbF) is a potent genetic modifier, and the γ-globin gene induction has proven to be a sustainable therapeutic approach for the management of β-thalassemia. In this study, we have evaluated the HbF induction ability of A. vasica in vitro and in vivo, and the identification of potential therapeutic compounds through a bioassay-guided approach. In vitro benzidine-Hb assay demonstrated strong erythroid differentiation of K562 cells by A. vasica extracts. Subsequently, an in vivo study with an aqueous extract of A. vasica (100 mg/kg) showed significant induction of the γ-globin gene and HbF production. While in the acute study, the hematological and biochemical indices were found to be unaltered at the lower dose of A. vasica. Following the bioassay-guided approach, two isolated compounds, vasicinol (1) and vasicine (2) strongly enhanced HbF levels and showed prominent cellular growth kinetics with ample accumulation of total hemoglobin in K562 cultures. High HbF levels were examined by immunofluorescence and flow cytometry analysis, concomitant with the overexpression in the γ-globin gene level. Compound 1 (0.1 µM) and compound 2 (1 µM) resulted in a greater increase in F-cells (90 and 83%) with marked up (8-fold and 5.1-fold) expression of the γ-globin gene, respectively. Molecular docking studies indicated strong binding affinities of (1) and (2) with HDAC2 and KDM1 protein that predict the possible mechanism of compounds in inhibition of these epigenetic regulators in the γ-globin gene reactivation. Altogether, these observations demonstrated the therapeutic usefulness of A. vasica for fostering HbF production in clinical implications for blood disorders.
Higher total faecal short-chain fatty acid concentrations correlate with increasing proportions of butyrate and decreasing proportions of branched-chain fatty acids across multiple human studies

Abstract Metabolites produced by microbial fermentation in the human intestine, especially short-chain fatty acids (SCFAs), are known to play important roles in colonic and systemic health. Our aim here was to advance our understanding of how and why their concentrations and proportions vary between individuals. We have analysed faecal concentrations of microbial fermentation acids from 10 human volunteer studies, involving 163 subjects, conducted at the Rowett Institute, Aberdeen, UK over a 7-year period. In baseline samples, the % butyrate was significantly higher, whilst % iso-butyrate and % iso-valerate were significantly lower, with increasing total SCFA concentration. The decreasing proportions of iso-butyrate and iso-valerate, derived from amino acid fermentation, suggest that fibre intake was mainly responsible for increased SCFA concentrations. We propose that the increase in % butyrate among faecal SCFA is largely driven by a decrease in colonic pH resulting from higher SCFA concentrations. Consistent with this, both total SCFA and % butyrate increased significantly with decreasing pH across five studies for which faecal pH measurements were available. Colonic pH influences butyrate production through altering the stoichiometry of butyrate formation by butyrate-producing species, resulting in increased acetate uptake and butyrate formation, and facilitating increased relative abundance of butyrate-producing species (notably Roseburia and Eubacterium rectale).
Statistical shape model of the spine fitting study: impact of clipping the latent representation

Statistical shape models (SSMs) represent the distribution of labeled points across a training set of shapes. The standard practice for SSMs based on principal component analysis (PCA) is to use clipping, thresholding the latent representation so that all shapes lie within 3 standard deviations of the mean. This practice precludes the representation of shapes that are not well represented by the training set, constraining the model to realistic solutions, but making it impossible to work with shapes at the edges of the statistical population. In this study, we investigate the impact of clipping in a PCA-based SSM and whether using L2 regularization is a good replacement for clipping in the context of the automatic 2D to 3D reconstruction of the spine. We first show that using L2 regularization is equivalent to using a probabilistic PCA with two error variables, accounting for the suppression of the least important principal components and for the fact that the training set cannot perfectly represent all shapes at test time. Secondly, we use two data sets of 1746 and 768 patients with adolescent idiopathic scoliosis to study the effect of regularization, for different regularization weights and with or without clipping, for removing landmark detection errors using a simulated noise or a reconstruction pipeline. In both sets of experiments, we show that regularization removes noise in a way similar to clipping without preventing the reconstruction of out-of-distribution shapes, leading to outputs closer to ground truth, demonstrating that using a regularized SSM should be preferred to clipping.
An unsupervised learning-based shear wave tracking method for ultrasound elastography

Shear wave elastography involves applying a non-invasive acoustic radiation force to the tissue and imaging the induced deformation to infer its mechanical properties. This work investigates the use of convolutional neural networks to improve displacement estimation accuracy in shear wave imaging. Our training approach is completely unsupervised, which allows to learn the estimation of the induced micro-scale deformations without ground truth labels. We also present an ultrasound simulation dataset where the shear wave propagation has been simulated via finite element method. Our dataset is made publicly available along with this paper, and consists in 150 shear wave propagation simulations in both homogenous and hetegeneous media, which represents a total of 20,000 ultrasound images. We assessed the ability of our learning-based approach to characterise tissue elastic properties (i.e., Young's modulus) on our dataset and compared our results with a classical normalised cross-correlation approach.
HOW TO PAVE THE ROAD TO A BETTER FUTURE FOR PHYSICAL EDUCATION

Reflecting on the approach to my assignment – (to speak about the “future of physical education (PE)”) – my first option was to deliver a paper focusing solely on a futuristic perspective. However, mindful of the Arab saying “prediction is difficult, in particular when it is about the future” and considering that I would not come much further than forcing open doors, e.g. forecasting that in the coming decade IT technology will become a major factor in the delivery of PE lessons, I dropped the idea of a futuristic approach. Instead I decided to present a paper that, starting from a solid theoretical basis, focuses on the question ‘what are the changes the PE profession needs to carry out in order to secure a solid position within the core curriculum of the schools of the future? ’. In keeping with the sentiment expressed in the motto above (borrowed from Santayana) my lecture on the future of PE will be solidly grounded in reflections and analysis on the past and the present status of PE. In the coming 40 minutes you can expect: 1. a brief description of symptoms of the current misery,
Replacing the Animal Component in Serum Evaluating Raw Materials for Inclusion in Optimized Hybridoma Media

www.pharmtech. com he next decade is expected to see a large increase in the use of antibodies as in vivo therapeutic agents. Currently, at least 200 antibodies or antibody fragments are undergoing clinical trials (1). Development of these biopharmaceuticals is increasing the focus on the need to use cellculture media that contain no serum or any other components of animal origin (2). Reasons for removing serum and other animalderived raw materials from media are varied and usually include a combination of such factors as component variabilities inherent in biological sources, possible contaminants, the high cost of serum, and downstream processing issues. Because of the biological nature of serum, both the quality and performance of the final products are subject to substantial variation. Serum and animalderived materials also have the potential for introducing contaminants and toxic elements such as viral particles and endotoxins (3). As a raw material, serum adds substantial cost to biopharmaceutical manufacturing. In addition, serum often interferes with final product purification, which increases the costs of downstream processing. Furthermore, regulatory issues associated with the use of biological materials in manufacturing processes are problematic; meeting those requirements also raises the final production costs. We used a three-stage approach in evaluating raw materials and optimizing the formulation of serum-free and animal component–free hybridoma media. In the first stage, we tested numerous agents for general growth characteristics and for gross toxicity limits in static culture using 24and 96-well plates. In the second stage, we optimized a complex mix of components for cell growth and antibody productivity using spinner flasks. We tested simple paired comparisons, concentration profiles, and factorial matrices, then analyzed the data using nonsubjective numerical methods and graphical techniques. In the third stage, we verified or further optimized the media while comparing them with competitor products and using various other cell lines and systems.
Adapted Fencing for Patients With Invasive Breast Cancer: The RIPOSTE Pilot Randomized Controlled Trial

Introduction Even if indications for mastectomy have been progressively reduced in loco-regional breast cancer (BC) treatment, the harmful effects of surgery are still numerous and can impact physical and psychological wellbeing of women. The RIPOSTE (Reconstruction, self-Image, Posture, Oncology, “Santé”-Health, Therapy, “Escrime”-Fencing) program aimed to propose adapted fencing to patients with BC. This study aims to investigate the effect and conditions of effectiveness of the RIPOSTE program. Methods and analysis This is a prospective randomized controlled trial including 24 patients with invasive BC who have just undergone surgery. The study will be proposed to the patient and if interested, the patient will be referred to a sports physician for a medico-sportive evaluation. At the end the evaluation, if the patient meets the inclusion criteria, she will be randomly assigned to one of the 2 groups based on a 1:1 principle: Early RIPOSTE group (receive one fencing session per week for 3 months immediately after their inclusion), Delayed RIPOSTE group (receive one fencing session per week for 3 months but within the 3 months following their inclusion). Patients will be included for 6 months with 3 follow-up times (0, 3, and 6 months) by a sport physician. The primary outcome is the evolution of quality of life score. Secondary outcomes are disability score, fatigue, anxiety-depression, cost-effectiveness and process evaluation. Ethics and dissemination The study protocol has been approved by a French ethics committee (CPP Sud Méditerranée IV, N°ID-RCB: 2020-A01916-33). Results will be submitted for publication, at scientific conferences and through press releases. Trial Registration NCT04627714.
Spatial modeling of dyadic geopolitical interactions between moving actors

Political actors often interact spatially, and move around. However, with a few exceptions, existing political research has analyzed spatial dependence among actors with fixed geographic locations. Focusing on fixated geographic units prevents us from probing dependencies in spatial interaction between spatially dynamic actors, which are common in some areas of political science, such as sub-national conflict studies. In this note, we propose a method to account for spatial dependence in dyadic interactions between moving actors. Our method uses the spatiotemporal histories of dyadic interactions to project locations of future interactions—projected actor locations (PALs). PALs can, in turn, be used to model the likelihood of future dyadic interactions. In a replication and extension of a recent study of subnational conflict, we find that using PALs improves the predictive performance of the model and indicates that there is a clear relationship between actors’ past conflict locations and the likelihood of future conflicts.