Silicon-Germanium multi-quantum well photodetectors in the near infrared

Cataloged from PDF version of article.Single crystal Silicon-Germanium multi-quantum well layers were epitaxially grown on silicon substrates. Very high quality films were achieved with high level of control utilizing recently developed MHAH epitaxial technique. MHAH growth technique facilitates the monolithic integration of photonic functionality such as modulators and photodetectors with low-cost silicon VLSI technology. Mesa structured p-i-n photodetectors were fabricated with low reverse leakage currents of ∼10 mA/cm2 and responsivity values exceeding 0.1 A/W. Moreover, the spectral responsivity of fabricated detectors can be tuned by applied voltage. © 2012 Optical Society of Americ

Antifungal and Bioherbicidal Properties of Essential Oils of Thymus fallax Fish & Mey., Origanum vulgare L. and Mentha dumetorum Schult.

WOS: 000343767000048The chemical composition of the essential oils obtained from the aerial parts of Thymus fallax, Origanum vulgare and Mentha dumetorum was analyzed by gas chromatography-mass spectrometry and the following were found to be the main constituents: T. fallax-thymol (41.48 %), o-cymene (26.75 %), zeta-terpinen (15.84 %), 2-isopropyl-1-methoxy-4-methylbenzene (5.10 %), terpineolene (2.11 %) and carvacrol (1.28 %); O. vulgare-thymol (50.41 %), carvacrol (12.96 %), 2-bornene (11.28 %), zeta-terpinen (8.80 %), o-cymene (6.68 %), alpha-bisabolane (2.19 %) and caryophyllene (1.31 %); and M. dumetorum-carvone (39.64 %), eucalyptol (14.34 %), dihydrocarvone (12.78 %), limonene (7.79 %). The antifungal activities of the oils against Alternaria solani, Fusarium oxysporum and Rhizoctonia solani were also evaluated and were found to be toxic to the pathogens. The results revealed that essential oils, especially those of T. fallax and O. vulgare, had a strong antifungal activity with a significant inhibition on the growth of the 3 tested fungi. In contrast, the M. dumetorum oil did not inhibit the growth of Rhizoctonia solani and also exerted a limited inhibitory effect on the mycelial growth of the other two fungi tested. The results of herbicidal assays using these essential oils against four different plant species, Abutilon theophrasti Medik., Agrostemma githago L., Medicago sativa L. and Lepidium sativum L., showed that the oils had inhibitory effects on seed germination and seedling growth. The findings of the present study confirmed that plant essential oils can be used as natural herbicides and fungicides to control weeds and pathogenic fungi, thus, reducing the dependence on synthetic pesticides

Detection of underdeveloped hazelnuts from fully developed nuts by impact acoustics

Shell-to-kernel weight ratio is a vital measurement of quality in hazelnuts as it helps to identify nuts that have underdeveloped kernels. Nuts containing underdeveloped kernels may contain mycotoxin-producing molds, which are linked to cancer and are heavily regulated in international trade. A prototype system was set up to detect underdeveloped hazelnuts by dropping them onto a steel plate and recording the acoustic signal that was generated when a kernel hit the plate. A feature vector comprising line spectral frequencies and time-domain maxima that describes both the time and frequency nature of the impact sound was extracted from each sound signal and used to classify each nut by a support-vector machine. Experimental studies demonstrated accuracies as high as 97% in classifying hazelnuts with underdeveloped kernels

Structure–activity study of N-((trans)-4-(2-(7-cyano-3,4-dihydroisoquinolin-2(1H)-yl)ethyl)cyclohexyl)-1H-indole-2-carboxamide (SB269652), a bitopic ligand that acts as a negative allosteric modulator of the dopamine D2 receptor

We recently demonstrated that SB269652 (1) engages one protomer of a dopamine D2 receptor (D2R) dimer in a bitopic mode to allosterically inhibit the binding of dopamine at the other protomer. Herein, we investigate structural deter- minants for allostery, focusing on modifications to three moieties within 1. We find that orthosteric “head” groups with small 7-substituents were important to maintain the limited negative cooperativity of analogues of 1, and replacement of the tetrahydroisoquinoline head group with other D2R “privileged structures” generated orthosteric antagonists. Additionally, replacement of the cyclohexylene linker with polymethylene chains conferred linker length dependency in allosteric pharma- cology. We validated the importance of the indolic NH as a hydrogen bond donor moiety for maintaining allostery. Replacement of the indole ring with azaindole conferred a 30-fold increase in affinity while maintaining negative cooperativity. Combined, these results provide novel SAR insight for bitopic ligands that act as negative allosteric modulators of the D2R

Detection of empty hazelnuts from fully developed nuts by impact acoustics

Shell-kernel weight ratio is the main determinate of quality and price of hazelnuts. Empty hazelnuts and nuts containing undeveloped kernels may also contain mycotoxin producing molds, which can cause cancer. A prototype system was set up to detect empty hazelnuts by dropping them onto a steel plate and processing the acoustic signal generated when kernels impact the plate. The acoustic signal was processed by five different methods: 1) modeling of the signal in the time domain, 2) computing time domain signal variances in short time windows, 3) analysis of the frequency spectra magnitudes, 4) maximum amplitude values in short time windows, and 5) line spectral frequencies (LSFs). Support Vector Machines (SVMs) were used to select a subset of features and perform classification. 98% of fully developed kernels and 97% of empty kernels were correctly classified

Wheat and hazelnut inspection with impact acoustics time-frequency patterns

Kernel damage caused by insects and fungi is one of the most common reason for poor flour quality. Cracked hazelnut shells are prone to infection by cancer producing mold. We propose a new adaptive time-frequency classification procedure for detecting cracked hazelnut shells and damaged wheat kernels using impact acoustic emissions recorded by dropping wheat kernels or hazelnut shells on a steel plate. The proposed algorithm is based on a flexible local discriminant bases (F-LDB) procedure. The F-LDB method combines local cosine packet analysis and a frequency axis clustering approach which supports individual time and frequency band adaptation. Discriminant features are extracted from the adaptively segmented acoustic signal, sorted according to a Fisher class separability criterion, post processed by principal component analysis and fed to linear discriminant. We describe experimental results that establish the superior performance of the proposed approach when compared with prior techniques reported in the literature or used in the field. Our approach achieved classification accuracy in paired separation of undamaged wheat kernels from IDK, Pupae and Scab damaged kernels with 96%, 82% and 94%. For hazelnuts the accuracy was 97.1%

Identification of damaged wheat kernels and cracked-shell hazelnuts with impact acoustics time-frequency patterns

A new adaptive time-frequency (t-f) analysis and classification procedure is applied to impact acoustic signals for detecting hazelnuts with cracked shells and three types of damaged wheat kernels. Kernels were dropped onto a steel plate, and the resulting impact acoustic signals were recorded with a PC-based data acquisition system. These signals were segmented with a flexible local discriminant bases (F-LDB) procedure in the time-frequency plane to extract discriminative patterns between damaged and undamaged food kernels. The F-LDB procedure requires no prior knowledge of the relevant time or frequency indices of the impact acoustics signals for classification. The method automatically finds all crucial time-frequency indices from the training data by combining local cosine packet analysis and a frequency axis clustering approach, which supports individual time and frequency band adaptation. Discriminant features are extracted from the adaptively segmented acoustic signal, sorted according to a Fisher class separability criterion, post-processed by principal component analysis, and fed to a linear discriminant classifier. Experimental results establish the superior performance of the proposed approach when compared to prior techniques reported in the literature or used in the field. The new approach separated damaged wheat kernels (IDK, pupal, and scab) from undamaged wheat kernels with 96%, 82%, and 94% accuracy, respectively. It also separated cracked-shell hazelnuts from those with undamaged shells with 97.1% accuracy. The adaptation capability of the algorithm to the time-frequency patterns of signals makes it a universal method for food kernel inspection that can resist the impact acoustic variability between different kernel and damage types. 2008 American Society of Agricultural and Biological Engineers

The Energy Landscape Analysis of Cancer Mutations in Protein Kinases

The growing interest in quantifying the molecular basis of protein kinase activation and allosteric regulation by cancer mutations has fueled computational studies of allosteric signaling in protein kinases. In the present study, we combined computer simulations and the energy landscape analysis of protein kinases to characterize the interplay between oncogenic mutations and locally frustrated sites as important catalysts of allostetric kinase activation. While structurally rigid kinase core constitutes a minimally frustrated hub of the catalytic domain, locally frustrated residue clusters, whose interaction networks are not energetically optimized, are prone to dynamic modulation and could enable allosteric conformational transitions. The results of this study have shown that the energy landscape effect of oncogenic mutations may be allosteric eliciting global changes in the spatial distribution of highly frustrated residues. We have found that mutation-induced allosteric signaling may involve a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. The presented study has demonstrated that activation cancer mutations may affect the thermodynamic equilibrium between kinase states by allosterically altering the distribution of locally frustrated sites and increasing the local frustration in the inactive form, while eliminating locally frustrated sites and restoring structural rigidity of the active form. The energy landsape analysis of protein kinases and the proposed role of locally frustrated sites in activation mechanisms may have useful implications for bioinformatics-based screening and detection of functional sites critical for allosteric regulation in complex biomolecular systems