Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving the Membrane Permeability of 5-Fluorouracil via Cocrystallization

Pharmaceutical cocrystallization is proposed as a new method to enhance membrane permeability of a BCS class III model drug, 5-fluorouracil (5FU). Three cocrystals of 5FU, 5FU/3-hydroxybenzoic acid (1), 5FU/4-aminobenzoic acid (2), and 5FU/cinnamic acid (3), were successfully synthesized by a slurry method or a liquid-assisted grinding process. Spectroscopic methods, thermal analysis, and X-ray diffraction were used to characterize these new forms. The permeability was studied using a Franz diffusion cell and silicone membrane. All of the cocrystals showed improved membrane permeability compared to free 5FU. The cumulative amount per unit area of permeated 5FU in the first 10 h for 1–3 was increased by 41, 70, and 83%, and the steady penetration rates of 1–3 were increased by 38, 66, and 79%, respectively, as compared to the pure drug. Structure–permeability correlation study finds a link between intermolecular interactions and molecular packing in cocrystals and their permeability behavior and has import.
Inter-firm power relations and working conditions under new production models

In investigating recent changes to the automotive industry production process, such as modularisation, our work emphasises the process of fragmentation of production as a configuring element of inter-firm power relationships, and as an explanatory element in working conditions. From a theoretical framework focused on power relations, we analyse by way of a selected case study how the capabilities of companies and their network positions, together with the agency of labour, shape the power relations that influence the evolution of working conditions. The study does indeed find relevant changes to inter-firm relationships, for example, within networks of assemblers and suppliers, but without a consequent re-balancing of power. This finding serves to explain differences in the evolution of working conditions between distinct companies, these conditions being fully functional to a strategy for profitability and thus difficult to reverse. JEL Codes: J31, L14, L62
An Approach to detect fault text in articles

The problem of Fault text (that contains fake news) has spread enormously in recent years. Social media is the major source for this type of news because it is easily and freely accessible to everyone and this type of news can be shared easily and rapidly, this enabled the widespread of news, so there is a need to detect this type of news. This news will mislead the users creating chaos and unrest. So the detection has become mandatory to avoid chaos and to maintain the pleasant news. We use Machine Learning Algorithms and basic Natural Language Process techniques to detect this type of news. In this work, Machine Learning Algorithms are used to parse the article and extract the summary from the article, this summary is used to predict the credibility. A passive-aggressive classifier and multinomial naive Bayes algorithms are used to train the model. A web app is created using the Flask API. One can put the URL in the web page to detect the news as “FAKE” or “REAL”.
Intestinal microbiota mediates the beneficial effects of n-3 polyunsaturated fatty acids during dietary obesity,

Obesity, now considered as a real worldwide epidemic affecting more than 650 million people, is complex and mainly associated with excessive energy intake and changes in eating habits favoring the consumption of diets rich in saturated fat and sugar. This multifactorial pathology is linked to chronic low grade systemic inflammation. Indeed, a high fat diet (HFD) leads to intestinal microbiota dysbiosis increasing gut permeability (partly attributed to a downregulation of genes encoding tight junction proteins) leading to an increase in bacterial lipopolysaccharides (LPS) levels so-called metabolic endotoxemia. Studies have shown that n-3 polyunsaturated fatty acids (PUFAs) are involved in the prevention of obesity and insulin resistance partly through synthesis of lipid mediators. While studies suggest that n-3 PUFAs are able to modulate the gut microbiota, others show no effect of n-3 treatments on intestinal homeostasis. In the present work, we showed that when fed a hypercaloric and obsogenic diet, compared with wild-type (WT) mice, fat-1 mice (with constitutive production of n-3 PUFAs) resist to dietary obesity and associated metabolic disorders, maintain an effective gut barrier function and exhibit greater phylogenic diversity. Moreover, fecal microbiota transplantation from fat-1 to WT mice reversed body weight gain, normalized glucose tolerance and intestinal permeability in association with prevention of alteration of the colon mucus layer. We can conclude that the n-3 PUFA-mediated alterations of gut microbiota contribute to the prevention of metabolic syndrome in fat-1 mice and may represent a promising strategy to prevent metabolic disease and preserve a lean phenotype.
Effect of water on the caking properties of different types of wheat flour

In this study, powder flow analyser was used to determine the caking characteristics of a different type of wheat flours. Besides the flour type as a variable, three levels of water percentage (12.5, 18.5 and 30 (% w.w.b)) were also tested. The presence of water with the powder plays a significant role in the way the cereals powders pack and flow. Although tapped bulk densities did not vary much, the water had a significant impact on the powder caking strength. The results showed that these parameters were increased significantly as the water level increased for all flours. It is also revealed that different flours cake differently when different levels of water are added. At the highest water content, the caking increase markedly for the flours. Plasticisation by addition of water to the food powder is believed to be the essential factor determining the results obtained.
Mironov Lagrangian cycles in algebraic varieties

We generalize a construction due to Mironov. Some time ago he presented new examples of minimal and Hamiltonian minimal Lagrangian submanifolds in and . His construction is based on the considerations of a noncomplete toric action of , where , on subspaces that are invariant with respect to the action of a natural antiholomorphic involution. This situation takes place for a rather broad class of algebraic varieties: complex quadrics, Grassmannians, flag varieties and so on, which makes it possible to construct many new examples of Lagrangian submanifolds in these algebraic varieties. Bibliography: 4 titles.
WiFED Mobile: WiFi Friendly Energy Delivery With Mobile Distributed Beamforming

Wireless RF energy transfer for indoor sensors is an emerging paradigm ensuring continuous operation without battery limitations. However, high power radiation within ISM band interferes with packet reception for existing WiFi devices. The paper proposes the first effort in merging RF energy transfer within a standards compliant 802.11 protocol, realizing practical and WiFi-friendly Energy Delivery with Mobile Transmitters (WiFED Mobile). WiFED Mobile architecture is composed of a centralized controller coordinating the actions of multiple energy transmitters (ETs), and deployed sensors that periodically requires charging. The paper first describes 802.11 supported protocol features that can be exploited by sensors to request energy and for ETs to participate in energy transfer. Second, it devises a controller-driven bipartite matching algorithm, assigning appropriate number of ETs to sensors for efficient energy delivery. Thirdly, it detects outlier sensors (OS), which have limited power reception from static ETs and utilizes mobile ETs (METs) to satisfy their charging cycles. The proposed in-band and protocol supported coexistence in WiFED Mobile is validated via simulations and partly in a software defined radio testbed, showing that METs reduce latency by 42% and improve throughput by 83% in scenarios where using only static ETs fails to satisfy charging cycles of OS.
Materials for Electrodes of Li-Ion Batteries: Issues Related to Stress Development

ABSTRACT Presently, rechargeable Li-ion batteries, possessing highest energy densities among all batte-ries, are used in a major fraction of all portable electronic devices. However, for bestowing the Li-ion batteries suitable for such advanced applications, further improvements in the energy densities (Li-capacities) and in the cycle life are essential. In a broader sense, this can be achieved by replacing the presently used electrode materials by materials possessing higher Li-capacities and minimization of the degradation of such materials with electrochemical cycling. It has been realized that the major reason for degradation in battery performance in terms of capacity with cycling is the disintegration/fragmentation of the active electrode materials due to stresses generated during Li-intercalation/de-intercalation in every cycle. Such stresses arise from the reversible volume changes of the active electrode materials during Li-insertion and removal. In quest of higher energy densities, replacement of the presently used graphitic carbon by potentially higher capacity metallic anode materials (like Si, Sn, and Al) is likely to further accrue this stress related disintegration due to ∼30 times higher volume changes experienced by such materials. It has also been recently realized that passivating layer formed on the surface of the electrodes also contributes toward the stress development. After briefly introducing the mechanistic aspects of Li-ion batteries, this article focuses on the reasons and consequences associated with stress developments in different electrode materials, highlighting the various strategies, in terms of designing new electrode com-positions or reducing the microstructural scale, that are being presently adopted to address the stress-related issues. Considering that experimental determination of such stresses is essential toward further progress in Li-ion battery research, this article introduces a recently reported technique developed for real-time measurement of such stresses. It finally concludes by raising some critical issues that need to be resolved through further research in this area.
Polarization Selective Electromagnetic-Induced Transparency in the Disordered Plasmonic Quasicrystal Structure

We report a resonant plasmonic quasicrystal structure that support multiple bands of electromagnetically induced transparency (EIT) at visible frequencies. The quasicrystal structure is formed by a planar array of thin gold nanodisks arranged in a square lattice. The essential aspect of this quasicrystal is the periodic disorder that couples higher order modes to the broad background resonant mode. It can be noted that the EIT response of disordered quasicrystals having diagonally symmetric unit cells is polarization independent. Conversely, the EIT responses in the quasicrystals are “polarization selective”, that can be useful for spectral filtering application. Dispersion engineering through light–matter interactions in quasicrystals will be interesting for various applications including sensing, display, switching, nonlinear, and slow-light devices.
Current Trends of Arsenic Adsorption in Continuous Mode: Literature Review and Future Perspectives

Arsenic is a toxic element for humans and a major pollutant in drinking water. Natural and anthropogenic sources can release As into water bodies. The countries with the greatest arsenic contamination issues lack the affordable technology to attain the maximum permitted concentrations. Adsorption can be a highly efficient and low-cost option for advanced water treatment, and the development of new cheap adsorbents is essential to expand access to water with a safe concentration of arsenic. This paper aims to review the state of the art of arsenic adsorption from water in continuous mode and the latest progress in the regeneration and recovery of arsenic. The disposal of the exhausted bed is also discussed. Fixed-bed column tests conducted with novel adsorbents like binary metal oxides and biosorbents achieved the highest adsorption capacities of 28.95 mg/g and 74.8 mg/g, respectively. Iron-coated materials presented the best results compared to adsorbents under other treatments. High recovery rates of 99% and several cycles of bed regeneration were achieved, which can aggregate economic value for the process. Overall, further pilot-scale research is recommended to evaluate the feasibility of novel adsorbents for industrial purposes.
Facile aromatic nucleophilic substitution (SNAr) reactions in ionic liquids: an electrophile–nucleophile dual activation by [Omim]Br for the reaction

A facile aromatic nucleophilic substitution (SNAr) reaction in recyclable [Omim]Br under relatively mild conditions has been described. An electrophile–nucleophile dual activation by [Omim]Br is also discovered based on control experiments, 1H NMR and IR spectroscopies. This chemistry provides an efficient and metal-free approach for the generation of Caryl–X (XS, N, O) bonds, many of which are significant synthetic intermediates or drugs, making this methodology attractive to both synthetic and medicinal chemistry.
Safety of engineering systems of buildings with limited heat supply

In case of emergencies in large heat supply systems, the water temperature in the supply line of the heat supply system is reduced. It is necessary to determine the acceptable duration of the heat supply system during an emergency, taking into account the thermal accumulation of the external fencing and variable water consumption in the hot water supply system. A study was made of the operating modes of the heat supply system in conditions of emergency heat supply from the CHP. The factors affecting the thermal regime of buildings with external fences of various constructions with limited heat supply are considered. A method has been developed for calculating the cooling rate of the inner surface of the outer fence and the temperature on this surface at a given point in time. Calculated dependencies are obtained to determine the acceptable duration of the heat supply system with limited heat supply. Application of the developed methodology can increase energy efficiency and contribute to the energy saving of buildings in the event of emergencies in the heat supply network.
Linear functional state bounding for linear positive singular systems with disturbances varying within a bounded set

In this paper, the problem of linear functional state bounding for linear positive singular system with an interval time‐varying delay is investigated for the first time. First, the authors present new conditions for positivity, regularity, impulse free, and the existence of componentwise bound for the state vector of the singular systems without disturbance. Based on the obtained results, and by using state transformations, we derive the smallest componentwise ultimate bound of the state vector of the linear positive singular system with bounded disturbances. Then, we propose some sufficient criteria for linear functional state bounding problems of the positive singular system with time‐varying delays by using some new mathematical techniques. Since the conditions are given in terms of the linear programming/Hurwit matrix/spectral abscissa, we can check them easily and compute directly the smallest componentwise ultimate bound. Finally, a numerical example is given to demonstrate the correctness and the effectiveness of the proposed methodology.
A Perspective on Modeling and Characterization of Transformations in the Blocky Nature of Olefin Block Copolymers

Traditional characterization methods are still unable to reveal the block structure of olefin block copolymers (OBCs). Therefore, when the predictability of our well-developed computer code (Mohammadi et al. Macromolecules, 2014, 47, 4778–4789) is extended, the blocky nature of OBCs is modeled and characterized. The expanded model could produce a diversity of macromolecules varying in the concentration of chain-shuttling agent, catalyst ratio, and monomer composition as key processing variables. The OBCs were screened and distinguished in view of chain-related specifics, i.e., chain length and chemical composition distribution, as well as block-related characteristics, i.e., number, length, and chemical composition of hard and soft blocks. A detailed picture of the blockiness was captured and visualized tracing transitions in the microstructure of copolymers, from the case corresponding to a blend copolymer (without any shuttling) to an OBC (with considerable shuttling) and then to random copolymers, refl.
Unstressed carbon-metal films deposited by thermionic vacuum arc method

A novel method based on thermo-ionic vacuum arc plasma was developed to grow metal-carbon zero stress films for MEMS applications. The method chosen to prepare metal-carbon films uses an electron beam emitted by an externally heated cathode accelerated by a high anodic voltage. Applying a high voltage (1-6 kV) between cathode and anode bright plasma was ignited in carbon atoms. In order to minimize the internal stress and to get films with increased adherence, interlayer and graded interlayer with Fe, Cr, Al and Ni was deposited. The prepared films were characterized by XPS, XRD, AFM and ellipsometry.
Increasing productivity and sustainability of corporate performance by using management control systems and intellectual capital accounting approach

The purpose of this article is to provide an overview of the literature covering the area of management control systems (MCS) and intellectual capital accounting approach in logistics and related these concepts to sustainability of corporate performance. Management control system (MCS) is system in companies which gathers and uses information to assess the performance of diverse company resources like human, physical, financial aspects of the companies. The application of a management control system in the field of quality management is found to be useful in explaining what changes are necessary to maintain high quality levels. The other useful method, for assessing the performance of diverse companies' resources like intangible assets is intellectual capital accounting approach. Intellectual capitals are intangible assets that create value for business units and are one of the main factors in creating competitive advantages for companies. Attention and focus on intellectual capitals in organizations and companies are one of the fundamental segments in value chain in the direction of value creation, and measurement and accurate disclosure of intellectual capital make managers and stakeholders successful in conducting the organization. The current study develops necessitates of using these methods for reach to corporate sustainability and sustainable development in companies.
Statistical Analysis of Landslide Susceptibility, Macerata Province (Central Italy)

Every year, institutions spend a large amount of resources to solve emergencies generated by hydrogeological instability. The identification of areas potentially subject to hydrogeological risks could allow for more effective prevention. Therefore, the main aim of this research was to assess the susceptibility of territories where no instability phenomena have ever been detected. In order to obtain this type of result, statistical assessments of the problem cannot be ignored. In this case, it was chosen to analyse the susceptibility to landslide using a flexible method that is attracting great interest in the international scientific community, namely the Weight of Evidence (WoE). This model-building procedure, for calculating landslide susceptibility, used Geographic Information Systems (GIS) software by means of mathematical operations between rasters and took into account parameters such as geology, acclivity, land use, average annual precipitation and extreme precipitation events. Thus, this innovative research links landslide susceptibility with triggering factors such as extreme precipitation. The resulting map showed a low weight of precipitation in identifying the areas most susceptible to landslides, although all the parameters included contributed to a more accurate estimate, which is necessary to preserve human life, buildings, heritage and any productive activity.
Impact of comparative climate change perceptions on antecedents of tourists’ adaptation intentions for a coastal destination in Taiwan

Abstract Although previous research has confirmed that climate change impacts tourism systems, few studies have explored the differences in tourists’ adaptation intentions in response to diverse climate change perceptions. Therefore, this study compared two tourist groups with high and low climate change perception levels to understand their adaptation intentions based on protection motivation theory. A valid sample totaling 696 domestic tourists visiting Kenting National Park in Taiwan was surveyed. The results revealed that the low-perception tourist group had externally-oriented adaptation, with the perceived external environment or information dissemination impacting adaptation intention. However, the high-perception tourist group’s adaptation intention was internally-oriented, relating to their self-control and personal core values. This study’s findings contribute to the literature on different psychological viewpoints for understanding tourists’ adaptation intentions based on the protection motivation theory in the context of climate change. Destination management organizations should consider the responding adaptation intention of different tourists and formulate corresponding environmental destination management strategies.
Deep learning based methods for estimating distribution of coalescence rates from genome-wide data

Demographic and population structure inference is one of the most important problems in genomics. Population parameters such as effective population sizes, population split times and migration rates are of high interest both themselves and for many applications, e.g. for genome-wide association studies. Hidden Markov Model (HMM) based methods, such as PSMC, MSMC, coalHMM etc., proved to be powerful and useful for estimation of these parameters in many population genetics studies. At the same time, machine and deep learning have began to be used in natural science widely. In particular, deep learning based approaches have already substituted hidden Markov models in many areas, such as speech recognition or user input prediction. We develop a deep learning (DL) approach for local coalescent time estimation from one whole diploid genome. Our DL models are trained on simulated datasets. Importantly, demographic and population parameters can be inferred based on the distribution of coalescent times. We expect that our approach will be useful under complex population scenarios, which cannot be studied with existing HMM based methods. Our work is also a crucial step in developing a deep learning framework which would allow to create population genomics methods for different genomic data representations.