Determination of free electron density in sequentially doped InxGa1-xAs by Raman spectroscopy

The advent and exponential growth of mobile computing has spurred greater emphasis on the adoption of III-V compound semiconductors in device architectures. The introduction of high charge carrier densities within InxGa1-xAs and the development of metrologies to quantitate the extent of doping have thus emerged as an urgent imperative. As an amphoteric dopant, Si begins to occupy anionic sites at high concentrations, thereby limiting the maximum carrier density that can be obtained upon Si doping of III-V semiconductors. Here, we present Raman results on sequentially doped In0.53Ga0.47As wherein sulfur monolayer doping is used to introduce additional carrier density to Si-doped samples. The sequential doping of Si and S allows for high carrier concentrations of up to 1.3 × 10(19) cm(-3) to be achieved without damaging the III-V lattice. The coupling of the plasmon in the doped samples to the longitudinal optic phonons allows Raman spectroscopy to serve as an excellent probe of the extent of dopant activation, charge carrier density, and the surface depletion region. In particular, the energy position of a high-frequency coupled mode (HFCM) that is detected above 400 cm(-1) is used to extract the free electron density in these samples. The extracted free electron densities are well correlated with measured sheet resistance values and the carrier densities deduced from Hall measurements.

Mycobacterium chelonae hand infection following ferret bite

We present a case of hand infection caused by Mycobacterium chelonae. The patient was a 58-year-old woman with Type II diabetes mellitus and stage 4 chronic kidney disease. The infection occurred following a ferret bite and had not responded to oral antibiotics in the primary care setting. She developed signs of pyogenic flexor tenosynovitis of the index and middle fingers of her left hand. Laboratory parameters showed high C-reactive protein, raised erythrocyte sedimentation rate and leucocytosis. Ultrasound imaging confirmed the clinical diagnosis. Plain radiographs showed no osseous involvement. The infection was treated with surgical debridement and broad spectrum parenteral antibiotics. The intra-operative tissue specimens were initially negative on aerobic and anaerobic cultures. Following transient improvement of her inflammatory parameters and clinical signs, she developed a recurrence with added features of osteomyelitis of the index and middle finger metacarpal heads on repeat radiographs. A revision surgical debridement of the flexor tenosynovitis and osteomyelitis with specific long-term antibiotic cover has led to resolution of the infection. Extended cultures of the tissue specimens at the regional laboratory confirmed the causative organism to be M. chelonae. To our knowledge, this is the first reported case of M. chelonae infection resulting from a ferret bite. This case reminds us of the need for a high index of suspicion for infection with uncommon pathogens following animal bites, especially in patients with altered immune status.

Tree-structured proportional hazards regression modeling

A method for fitting piecewise proportional hazards models to censored survival data is described. Stratification is performed recursively, using a combination of statistical tests and residual analysis. The bootstrap is employed to keep the probability of a Type I error (the error of discovering two or more strata when there is only one) of the method close to a predetermined value. The proposed method can thus also serve as a formal goodness-of-fit test for the proportional hazards model. Real and simulated data are used for illustration.

Fine-needle aspiration for breast mass diagnosis

Our accuracy in diagnosing 464 solid breast masses by fine-needle aspiration was enhanced by a statistically based algorithm for distinguishing between benign and malignant epithelial cells. Epithelial cells were obtained from 378 breast masses by fine-needle aspiration; nonepithelial cells considered diagnostic of benign conditions were obtained from 66 breast masses, and 19 aspirations were considered unsatisfactory. Excluding one benign cystosarcoma, the algorithm gave 3 false-negative diagnoses and 16 false-positive diagnoses with 211 benign and 167 malignant samples. The overall clinical performance measures for the 444 masses from which diagnostic fine-needle aspirations were obtained and excluding the cystosarcoma were 0.98 sensitivity, 0.94 specificity, and 0.92 positive predictability. Masses diagnosed as benign by fine-needle aspiration can be followed up clinically. Intraoperative frozen section is needed before definitive surgery to determine invasion and confirm the diagnosis of some cytologically malignant masses.

Diagnostic schemes for fine needle aspirates of breast masses

A comparison was made of four statistically based schemes for classifying epithelial cells from 243 fine needle aspirates of breast masses as benign or malignant. Two schemes were computer-generated decision trees and two were user generated. Eleven cytologic characteristics described in the literature as being useful in distinguishing benign from malignant breast aspirates were assessed on a scale of 1 to 10, with 1 being closest to that described as benign and 10 to that described as malignant. The original computer-generated dichotomous decision tree gave 6 false negatives and 12 false positives on the data set; another tree generated from the current data improved performance slightly, with 5 false negatives and 10 false positives. Maximum diagnostic overlap occurred at the cut-point of the original dichotomous tree. The insertion of a third node evaluating additional parameters resulted in one false negative and seven false positives. This performance was matched by summing the scores of the eight characteristics that individually were most effective in separating benign from malignant. We conclude that, while statistically designed, computer-generated dichotomous decision trees identify a starting sequence for applying cytologic characteristics to distinguish between benign and malignant breast aspirates, modifications based on human expert knowledge may result in schemes that improve diagnostic performance.

Statistical approach to fine needle aspiration diagnosis of breast masses

A statistical algorithm was used for recursively partitioning a consecutive series of 37 benign and 69 malignant fine needle aspirates to produce a decision tree for diagnosing breast masses. Optimal separation between benign and malignant cytology was accomplished by evaluating clump characteristics when clumps were present and evaluating cell integrity when clumps were absent. The 1.5% false-negative and 9.7% false-positive rates obtained through this scheme are better than those reported for most series.