Amoxicillin Magadiite Derivatives: Advanced Materials for Antibacterial and Drug Delivery Applications

Silicon - Herein, a pure and well crystallized Na-magadiite was synthesized by hydrothermal method. It was then used as a host matrix to prepare hybrid materials by intercalation of zwitterionic...     

A hybrid Bayesian-frequentist predictive design for monitoring multi-stage clinical trials

Abstract

In this article, we propose a hybrid-Bayesian frequentist approach using a Bayesian sequential prediction of the index of satisfaction. For interim analysis that addresses prediction hypothesis, such as futility monitoring with delayed outcomes, the prediction of satisfaction properly accounts for the amount of data remaining to be observed in a clinical trial and has the flexibility to incorporate additional information via auxiliary variables. The prediction of satisfaction design guarantees the type I error rate and does not require intensive computation or comprehensive simulation. The design is retrospectively applied to a lung cancer clinical trial.     

Artificial neural network model for steel–concrete bond prediction

In this paper, an Artificial Neural Network (ANN) is proposed for modelling the bond between conventional ribbed steel bars and concrete. The purpose is to predict the ultimate pull-out load from the concrete mix constituents (first ANN model) or the compressive strength (second ANN model) and from the steel bar diameter according to the RILEM test configuration [RILEM. Essai portant sur l’adhérence des armatures du béton: essai par traction. Materials and Structures 1970; 3 (3) 175–78]. The ANN models were implemented using an experimental database of 112 pull-out test results performed with ribbed bars 10 mm or 12 mm in diameter and three concrete mixes with different constituent proportions. A Multi-Layer-Perceptron was trained according to a back-propagation algorithm. The first model has six inputs (ANN-6): the diameter of the ribbed bar, the water to cement ratio, the gravel to sand ratio, the crushed to rolled gravel ratio, the type of cement and the concrete maturity. The second model has two inputs (ANN-2): the diameter of the bar and the concrete compressive strength. The ultimate pull-out load was the output data for both models.The results show that the implemented models have good prediction and generalisation capacity with low errors. The ANN-6 model is more accurate, regarding the generalisation capacity, than the ANN-2 model. Concrete mix constituents as input parameter, instead of the compressive strength, are more representative of the local phenomenon at the steel-ribs-to-concrete interface.     

Physicochemical,Phytochemical and Mycological Characteristics of Italia Muscat Raisins Obtained Using Different Pre-treatments and Drying Techniques

Raisins represent an economically important grapevine by-product. However, their quality is largely dependent on drying techniques and processing conditions. In this context, two drying processes were monitored: hot air drying in a convective oven and greenhouse drying. Grape berries were previously subjected to two chemical pre-treatments (olive oil and K₂CO₃ emulsion dipping (I) and NaOH solution bleaching (II)). Pre-treated grapes processed using both methods were compared with sun-dried samples. The results show that oven drying was more efficient and rapid (5 days) as compared with greenhouse drying (13 days). The end moisture content of grapes varied from 16.12% to 22.25% on a wet basis in dried samples, respectively. Significant differences in the pH value (3.85–4), acidity (1172.5–2730 mg TA/100 g DW) and total sugars (31.5–49.7%) were also observed, between raisin samples subjected to both treatments and drying methods, whereas protein levels (1–1.25%) were not affected. The analysis of minerals indicates that greenhouse-dried raisins had high amounts of calcium (Ca), magnesium (Mg) and sodium (Na). The highest polyphenol (417.70 mg GAE/100 g DW), flavonoid (115.87 mg CE/100 g DW) and tannin (368.13 mg CE/100 g DW) contents were recorded in sun-dried samples, respectively. The distribution of fungal flora shows a noteworthy variability among raisin samples, with a marked abundance of ochratoxinogenic species such as Aspergillus ochraceus and Aspergillus carbonarius (15.56% and 10.41%, respectively). Italia Muscat raisins processed using oven drying could be an economically interesting alternative to manage the excessive grapes production and consequently solve related marketing issues.     

Investigation of structural,optical, antibacterial,and dielectric properties of V-doped copper oxide thin films: Comparison with undoped copper oxide thin films

Vanadium doped Copper oxide (CO) thin films were prepared by the sol-gel dip-coating method. The properties of thin films were examined by X-Ray Diffractometer (XRD), UV–Visible-NIR spectrophotometry, and dielectric properties analyzer. The antibacterial and photocatalytic properties were also determined. XRD spectra revealed the dual-phase of copper oxide (cuprite and tenorite) for all percentages of V with no other impurity peak. Tauc's relation is used to probe the optical band gap which is reduced from 1.96 to 1.64 eV with an increase in vanadium doping percentage. The impurity band coalesces with the conduction band of copper oxide to decrease the band gap. Dielectric constant measurements reveal that the Ac conductivity of thin films increases with an increase in V doping percentage.     

A Predictive Model of the Optimal Tool Edge Geometry for Veneer Cutting Processes

Abstract

Veneer cutting is a specific machining process, where the chip is the final product. The objective of this article is to investigate on the optimal tool edge geometry, using particle swarm optimization (PSO) algorithm, to obtain the desired veneer thickness. The challenge is to maintain the best quality of veneer product with the control of pre-splitting condition and thickness variation. Numerical results obtained from PSO algorithm are compared and verified with the experimental ones. The proposed model allows us to predict the characteristic tool angles for different chip thicknesses and friction coefficients. For chip thickness range greater than 2?mm, the presplitting condition is no longer satisfied, as in the case of rotary peeling veneer, the need of using pressure bar becomes primordial.     

Total Phenolics, Flavonoids, and Antioxidant Activity of Sage (Salvia officinalis L.) Plants as Affected by Different Drying Methods

In the current study, we determined the effects of seven drying methods on total phenolics, flavonoids, individual phenolics, and antioxidant activity of the methanol extract of Salvia officinalis L. As compared with total phenolic content (TPC) of fresh plants, results showed that the highest TPC was recorded in plants dried by microwave (MW) at a power of 800 W/30 g of fresh plant and was 4.2 times higher than that of fresh plants whereas the lowest content was found in the case of plants dried by far-infrared (FIR) at 45 °C. The analysis of the different extracts by RP-HPLC showed a predominance of phenolic acids particularly in fresh plants and those dried by MW (600 W/30 g of fresh plant) whereas flavonoids predominate in the case of plants dried by FIR (65 °C). The assessment of the radical scavenging activity (RSA) against the stable radical 1,1-diphenyl-1-picrylhydrazyl (DPPH) showed an increase in the scavenging effect particularly in MW (800 W/30 g of fresh plant) dried plants with an IC50?=?13.49 μg ml^?1 (IC50 is the concentration required to cause 50 % DPPH inhibition). The complementary assessment of the RSA using the β-carotene/linoleic acid system showed an increase of this activity for all extracts and particularly for the extract derived from MW (600 W/30 g of fresh plant) dried plants as compared to fresh ones. Finally, all the plant extracts showed moderate reducing power as assessed by the ferric-reducing antioxidant potential. These results suggested that MW drying could be applied to retain phenolic contents and to enhance antioxidant activity of sage plant materials.     

In vitro evaluation of bioactivity of SiO2-CaO-P2O5-Na2O-CaF2-ZnO glass-ceramics

Zinc is an essential trace element that stimulates bone formation but it is also known as an inhibitor of apatite crystal growth. In this work addition of ZnO to SiO₂-CaO-P₂O₅-Na₂O-CaF₂ glass-ceramic system was made by conventional melt-quenching technique. DSC curves showed that the addition of ZnO moved the endothermic and exothermic peaks to lower temperatures. X-ray diffraction analysis did not reveal any additional phase caused by ZnO addition and showed the presence of wollastonite and hydroxyapatite crystalline phases only in all the glass-ceramic samples. As bio-implant apatite forming ability is an essential condition, the surface reactivity of the prepared glass-ceramic specimens was studied in vitro in Kokubo’s simulated body fluid (SBF) [1] with ion concentration nearly equal to human blood plasma for 30 days at 37 °C under static condition. Atomic absorption spectroscopy (AAS) was used to study the changes in element concentrations in soaking solutions and XRD, FT-IR and SEM were used to elucidate surface properties of prepared glass-ceramics, which confirmed the formation of HCAp on the surface of all glass-ceramics. It was found that the addition of ZnO had a positive effect on bioactivity of glass-ceramics and made it a potential candidate for restoration of damaged bones.     

Fast distributed multi-hop relative time synchronization protocol and estimators for wireless sensor networks

The challenging problem of time synchronization in wireless sensor networks is considered in this paper, where a new distributed protocol is proposed for both local and multi-hop synchronization. The receiver-to-receiver paradigm is used, which has the advantage of reducing the time-critical-path and thus improving the accuracy compared to common sender-to-receiver protocols. The protocol is fully distributed and does not rely on any fixed reference. The role of the reference is divided amongst all nodes, while timestamp exchange is integrated with synchronization signals (beacons). This enables fast acquisition of timestamps that are used as samples to estimate relative synchronization parameters. An appropriate model is used to derive maximum likelihood estimators (MLE) and the Cramer-Rao lower bounds (CRLB) for both the offset-only, and the joint offset/skew estimation. The model permits to directly estimating relative parameters without using or referring to a reference’ clock. The proposed protocol is extended to multi-hop environment, where local synchronization is performed proactively and the resulted estimates are transferred to the intermediate/end-point nodes on-demand, i.e. as soon as a multi-hop communication that needs synchronization is initiated. On-demand synchronization is targeted for multi-hop synchronization instead of the always-on global synchronization model, which avoids periodic and continuous propagation of synchronization signals beyond a single-hop. Extension of local MLE estimators is proposed to derive relative multi-hop estimators. The protocol is compared by simulation to some state-of-the-art protocols, and results show much faster convergence of the proposed protocol. The difference has been on the order of more than twice compared to CS-MNS, more than ten times compared to RBS, and more than twenty times compared to TPSN. Results also show scalability of the proposed protocol concerning the multi-hop synchronization. The error does not exceed few microseconds for as much as 10 hops in R4Syn, while in CS-MNS, and TPSN, it reaches few tens of microseconds. Implementation and tests of the protocol on real sensor motes confirm microsecond level precision even in multi-hop scenarios, and high stability (long lifetime) of the skew/offset model.