Prevalence of adrenal carcinoma among incidentally discovered adrenal masses. A retrospective study from 1989 to 1994. Gruppo Piemontese Incidentalomi Surrenalici

BACKGROUND: The incidental discovery of an adrenal mass poses the problem of distinguishing between the frequent benign masses and the infrequent malignant ones that require surgery. Univocal guidelines to approach this problem are unavailable. OBJECTIVE: To perform a survey of the clinical management of incidentally discovered adrenal masses (ie, adrenal incidentalomas). DESIGN: A multicentric retrospective analysis of hospital medical records of adrenal incidentalomas diagnosed during a 5-year period; the medical records were scrutinized for demographic data and clinical details by means of a specifically tailored questionnaire. SETTING: The major surgical and medical centers of Piedmont, a northern Italian region with approximately 4 million inhabitants. The recruitment pattern of these centers was unselected. PATIENTS: The definition of adrenal incidentaloma was limited to patients with a physical examination and a clinical history unindicative of adrenal disease. Exclusion criteria also included hypertension of suspected endocrine origin and a history of neoplasms known to metastasize frequently in the adrenal glands. Two hundred twenty-four medical records were collected, and 210 were analyzed (14 excluded a posteriori). RESULTS: Most patients were in their 50s and 60s, and women were predominantly affected. The frequency of adrenocortical cancer was 13% among patients operated on. The tumor diameter was highly correlated with the risk of cancer; a cutoff at 5 cm had a sensitivity of 93% with a specificity of 64% in discriminating between benign and malignant cortical lesions. CONCLUSIONS: The occurrence of adrenocortical carcinoma among adrenal incidentalomas is not rare. The evaluation of the mass size is a simple and effective method for selecting patients at risk for cancer. The indication for surgery of masses larger than 5 cm, or of masses of any diameter that have suspicious imaging characteristics, limits unnecessary operations and costs.     

Asymmetric dilation of multiwavelength cross-connect switches forlow-crosstalk WDM optical networks

We predict that, for wavelength division multiplexing optical-network applications, an asymmetrically dilated configuration of a 2×2 cross-connect is significantly better in terms of overall crosstalk when the levels of the bar-port crosstalk and the cross-port crosstalk are significantly different from each other, as is the case with optical-frequency filters which utilize grating-assisted coupling. As a verification, we present a simulation study with 2×2 polarization-diversified acousto-optic tunable filters. We present a recursive method to extend the principle of asymmetric dilation to larger-size cross-connect switches, and make a recommendation for an asymmetrically dilated 4×4 cross-connect configuration     

Positive temperature dependence of the electron impact ionizationcoefficient in In0.53Ga0.47As/InP HBTs

Impact ionization is a major limiting factor to the maximum operating voltage of InGaAs-based, high-speed transistors. In this work, data on the positive temperature dependence of the electron impact ionization coefficient α_n in In_0.53Ga_0.47As at medium-low electric fields are reported for the first time. The increase of α_n with temperature is opposite to the behavior normally observed in most semiconductors. This anomalous behavior implies the onset of a positive feedback between power dissipation and avalanche generation which may adversely affect the power handling capability of In_0.53Ga _0.47As-based devices, and which should be taken into account in device thermal modeling. In the experimental procedure, based on the measurement of the multiplication factor M-1 in npn In_0.53Ga _0.47As/InP Heterojunction Bipolar Transistors (HBT), particular care has been taken in order to rule out possible spurious, temperature-dependent contributions to the measured multiplication current     

Application of neural networks and machine learning in networkdesign

Communication network design is becoming increasingly complex, involving making networks more usable, affordable, and reliable. To help with this, we have proposed an expert network designer (END) for configuring, modeling, simulating, and evaluating large structured computer networks, employing artificial intelligence, knowledge representation, and network simulation tools. We present a neural network/knowledge acquisition machine-learning approach to improve the END's efficiency in solving the network design problem and to extend its scope to acquire new networking technologies, learn new network design techniques, and update the specifications of existing technologies     

Series equivalence/operation of current-controlled boost-typesingle-phase voltage source converters for bidirectional power flow

Single-phase voltage source power converters (VSCs) under consideration are AC-DC current-controlled boost-type power converters with bidirectional power-handling capability. Equivalence between two series-connected two-level power converters and a single three-level power converter is considered here. Further considered is the series operation of three-level power converters. Simulation results and experimental verification for both are provided. Economical configurations of three-level power converters leading to multilevel waveforms are presented thereafter     

Low-truncation-error finite difference equations for photonicssimulation. II. Vertical-cavity surface-emitting lasers

For part I see, ibid., p. 134, 1998. The basic approach outlined in the previous article is applied to the difficult problem of computing the optical modes of a vertical-cavity surface-emitting laser. The formulation utilizes a finite difference equation based upon the lowest order term of an infinite series solution of the scalar Helmholtz equation in a local region. This difference equation becomes exact in the one-dimensional (1-D) limit, and is thus ideally suited for nearly 1-D devices such as vertical-cavity lasers. The performance of the resulting code is tested on both a simple cylindrical cavity with known solutions and an oxide-confined vertical-cavity laser structure, and the results compared against second-order-accurate code based upon Crank-Nicolson differencing     

Function materialization in object bases: design, realization, andevaluation

View materialization is a well-known optimization technique of relational database systems. We present a similar, yet more powerful, optimization concept for object-oriented data models: function materialization. Exploiting the object-oriented paradigm-namely, classification, object identity, and encapsulation-facilitates a rather easy incorporation of function materialization into (existing) object-oriented systems. Only those types (classes) whose instances are involved in some materialization are appropriately modified and recompiled, thus leaving the remainder of the object system invariant. Furthermore, the exploitation of encapsulation (information hiding) and object identity provides for additional performance tuning measures that drastically decrease the invalidation and rematerialization overhead incurred by updates in the object base. First, it allows us to cleanly separate the object instances that are irrelevant for the materialized functions from those that are involved in the materialization of some function result, and this to penalize only those involved objects upon update. Second, the principle of information hiding facilitates fine-grained control over the invalidation of precomputed results. Based on specifications given by the data type implementor, the system can exploit operational semantics to better distinguish between update operations that invalidate a materialized result and those that require no rematerialization. The paper concludes with a quantitative analysis of function materialization based on two sample performance benchmarks obtained from our experimental object base system GOM     

RAPS: a rule-based language for specifying resource allocation andtime-tabling problems

A general language for specifying resource allocation and time-tabling problems is presented. The language is based on an expert system paradigm that was developed previously by the authors and that enables the solution of resource allocation problems by using experts' knowledge and heuristics. The language enables the specification of a problem in terms of resources, activities, allocation rules, and constraints, and thus provides a convenient knowledge acquisition tool. The language syntax is powerful and allows the specification of rules and constraints that are very difficult to formulate with traditional approaches, and it also supports the specification of various control and backtracking strategies. We constructed a generalized inference engine that runs compiled resource allocation problem specification language (RAPS) programs and provides all necessary control structures. This engine acts as an expert system shell and is called expert system for resource allocation (ESRA). The performance of RAPS combined with ESRA is demonstrated by analyzing its solution of a typical resource allocation problem