This review covers several basic methodologies of surface treatment and their effects on titanium (Ti) implants. The importance of each treatment and its effects will be discussed in detail in order to compare their effectiveness in promoting osseointegration. Published literature for the last 18 years was selected with the use of keywords like titanium dental implant, surface roughness, coating, and osseointegration. Significant surface roughness played an important role in providing effective surface for bone implant contact, cell proliferation, and removal torque, despite having good mechanical properties. Overall, published studies indicated that an acid etched surface-modified and a coating application on commercial pure titanium implant was most preferable in producing the good surface roughness. Thus, a combination of a good surface roughness and mechanical properties of titanium could lead to successful dental implants.

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Surface Modifications and Their Effects on Titanium Dental Implants

Antibacterial titanium surfaces for medical implants

Nano-scale modification of titanium implant surfaces to enhance osseointegration

A critical review of multifunctional titanium surfaces: New frontiers for improving osseointegration and host response, avoiding bacteria contamination.

The use of porous silicon (PSi) as a sensor for detection of various analytes is reviewed. The optical or electrical properties of PSi are key sensing parameters that have been used in many chemical and biological sensing applications. PSi is a promising candidate due to ease of fabrication, large surface area, various accessible pore sizes and morphologies, controllable surface modification and its compatibility with conventional silicon processing technology. The adsorption of chemical or biological molecules into the pores modifies the electrical and/or optical properties, allowing convenient and sensitive measurement approach. In this review, we provide a critical assessment of the development of PSi as a promising material for chemical and biosensing applications. Formation procedures of PSi with various pore sizes and morphologies are firstly given. Surface properties and structural characteristics of the material are briefly described. The recent progress on utilization of such porous structures in chemical and biosensing applications is then addressed in the context of surface chemistry effects and nanostructures, measuring approaches, operating concepts and device sensitivity and stability. Finally, concluding remarks with existing challenges that hinder the material for commercial use are highlighted.

Porous silicon chemical sensors and biosensors: A review

The objective of this study is to investigate the potential of non-destructive techniques associated with chemometric data analysis for discriminating between Arabica and Robusta species coffee samples, and between Arabica coffee treated through two different processes. A total of 227 green coffee samples were analyzed by a FT-NIR spectrometer; electronic tongue investigation was simultaneously achieved on the same samples roasted and extracted in hot water. The spectroscopic technique was used to investigate differences between beans chemical composition, while electronic tongue evaluated diversity in the extract sample taste profile. Principal Component Analysis (PCA) was applied to spectral and electronic tongue data, as an exploratory tool to uncover correlations between samples. Linear discriminant analysis is used to classify coffee samples on the basis of the species and of the different treatments for Arabica samples. The results shows the ability of near-infrared methodology to classify these three typology of coffee, while electronic tongue approach generates a whole depiction of the taste profile. The spectroscopic methods result to be a reliable, cheap and fast classification tool, not requiring chemical analyses for discrimination among species; at the same time electronic tongue profile can be elaborated with the aim of better characterize coffee chemical composition

Discrimination of Arabica natural, Arabica washed and Robusta coffee through NIR spectroscopy and artificial tongue analysis

. Establishing the optimal harvest time is a fundamental issue for apple fruit industry, since fruit shelf life and quality are related to the ripening stage at harvest. Ripening indexes determination through destructive analysis is invasive for fruits and is limited to a low sample number. This work is focused on the study of red apples ripening (Scarlet variety ), with the aim of better identifying harvest date characterizing each stage of fruit ripening on trees using classical analysis and non–destructive analysis. UV-Vis spectroscopy is performed in diffuse reflectance mode to monitor variation of chlorophyll concentration in the skin of apples during ripening on trees; in fact, in the case of fruits as red apples the colour variation is hardly visible as ripening goes on, and ground colour cannot be considered a valid tool of ripening identification. Conversely chlorophyll monitoring using DRS-UV-Vis spectroscopy appears to be a reliable indicator of the ripeness level. Keywords. NIR and UV-Vis spectroscopy, diffuse reflectance, chlorophyll, ripening index, red apples.

Monitoring harvesting degree of red Scarlet apples using DR-UV-Vis and NIR spectroscopy

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Determinazione della concentrazione di pigmenti in matrici alimentari mediante analisi UV-VIS

L'obiettivo di questo lavoro e quello di valutare le potenzialita della spettroscopia nel vicino infrarosso (FT-NIR) associata ad un'analisi di tipo chemiometrico come metodo non distruttivo per la classificazione di diverse varieta di riso. Il riso (Oryza sativa L.) e un alimento basilare per l'alimentazione umana, che contribuisce al sostentamento di due terzi della popolazione mondiale. In termini di qualita finale del prodotto, la varieta e un fattore fondamentale, che implica differenze in termini di dimensioni, forma e composizione. Una gestione del raccolto non ottimale puo determinare una limitata purezza varietale e di conseguenza una drastica riduzione della qualita. Emerge dunque la necessita di elaborare un metodo veloce, accurato e non distruttivo per classificare il riso appartenente a differenti cultivar. Per questo studio sono stati usati 72 campioni di riso grezzo (risone) e 72 campioni di riso lavorato; si utilizzano due varieta aromatiche (Venere e Apollo) e sei varieta non aromatiche (Carnaroli, Carnise, Carnise precoce, Selenio, Cerere, Antares). La risaia sperimentale si trova a Trino (VC). L'identificazione della varieta di riso viene realizzata attraverso l'elaborazione di un modello predittivo, che comprende campioni sottoposti a diverse condizioni per rappresentare una piu ampia variabilita sperimentale. I contributi spettrali sono stati acquisiti mediante uno spettrofotometro MPA (Bruker Optics, Germania) nel range NIR da 12500 a 3500 cm-1, in modalita di riflettanza. I dati spettrali sono stati elaborati ed analizzati mediante tecniche chemiometriche, che prevedono un pre-trattamento degli spettri (smoothing e SNV), e l'applicazione di algoritmi di classificazione (SIMCA e LDA). Questo studio vuole dimostrare l'applicabilita della spettroscopia FT-NIR come tecnica rapida e non-distruttiva, volta all'identificazione delle varieta di riso nei test di routine. Il modello elaborato e stato inoltre utilizzato per caratterizzare una nuova varieta di riso e verificare quanto le sue caratteristiche siano comparabili a quelle di una nota varieta commerciale

Alberto Venturello

Papers

Discrimination of Arabica natural, Arabica washed and Robusta coffee through NIR spectroscopy and artificial tongue analysis

Monitoring harvesting degree of red Scarlet apples using DR-UV-Vis and NIR spectroscopy

Determinazione della concentrazione di pigmenti in matrici alimentari mediante analisi UV-VIS

Applicazione della spettroscopia FT-NIR per un’identificazione rapida e non distruttiva di diverse varietà di riso e risone

Monitoring Harvesting degree of red ‘Scarlet’ Apples using DR-UV–Vis and NIR Spectroscopy