On Hardware Implementation of Tang-Maitra Boolean Functions

In this paper, we investigate the hardware circuit complexity of the class of Boolean functions recently introduced by Tang and Maitra (IEEE-TIT 64(1): 393 402, 2018). While this class of functions has very good cryptographic properties, the exact hardware requirement is an immediate concern as noted in the paper itself. In this direction, we consider different circuit architectures based on finite field arithmetic and Boolean optimization. An estimation of the circuit complexity is provided for such functions given any input size n. We study different candidate architectures for implementing these functions, all based on the finite field arithmetic. We also show different implementations for both ASIC and FPGA, providing further analysis on the practical aspects of the functions in question and the relation between these implementations and the theoretical bound. The practical results show that the Tang-Maitra functions are quite competitive in terms of area, while still maintaining an acceptable level of throughput performance for both ASIC and FPGA implementations

The design and implementation of the LogicBlox system

The LogicBlox system aims to reduce the complexity of software development for modern applications which enhance and automate decision-making and enable their users to evolve their capabilities via a ``self-service'' model. Our perspective in this area is informed by over twenty years of experience building dozens of mission-critical enterprise applications that are in use by hundreds of large enterprises across industries such as retail, telecommunications, banking, and government. We designed and built LogicBlox to be the system we wished we had when developing those applications. In this paper, we discuss the design considerations behind the LogicBlox system and give an overview of its implementation, highlighting innovative aspects. These include: LogiQL, a unified and declarative language based on Datalog; the use of purely functional data structures; novel join processing strategies; advanced incremental maintenance and live programming facilities; a novel concurrency control scheme; and built-in support for prescriptive and predictive analytics.</p

Association of Insurance Status with the Use of Immediate Breast Reconstruction in Women with Breast Cancer

Background:. Our group sought to determine the influence of health insurance coverage on use of immediate breast reconstruction for working-age women undergoing mastectomy for breast cancer. Methods:. We used 2 complementary databases, the Texas Cancer Registry–linked Medicaid database and the MarketScan private insurance database, to identify working-age women in Texas from 2000 to 2007 treated with mastectomy for incident breast cancer. Logistic regression tested the association between Medicaid versus private insurance and receipt of immediate breast reconstruction, adjusting for patient, treatment, and socio-demographic covariates. Reimbursement for reconstruction, adjusted for inflation and reported in 2014 dollars, was estimated from claims. Results:. Median age was 49.7 years for the Medicaid cohort compared with 50.4 years for the MarketScan cohort (P = 0.02). From 2000 to 2007, use of reconstruction increased significantly for patients in the MarketScan cohort (38.1–53.9%; Ptrend = 0.009) but not those in the Medicaid cohort (10.5–16.6%; Ptrend = 0.24). In total, 15.7% of patients in the Medicaid cohort underwent immediate reconstruction (n = 213/1,360) compared with 50.7% (n = 1,405/2,772) of patients in the MarketScan cohort (adjusted relative risk, 3.09; 95% CI, 2.78–3.40). Reimbursement for reconstruction was $3,167 (95$2,512–$3,820) for patients in the Medicaid cohort compared with$15,432 (95% CI, $14,030–$16,834) for patients in the MarketScan cohort. Conclusions:. Type of insurance coverage is an important factor associated with receipt of immediate breast reconstruction. We postulate that the marked difference in reimbursement for reconstruction between Medicaid and private insurance creates a relative disincentive for plastic surgeons and hospitals to offer breast reconstruction to patients with Medicaid

Statically Safe Program Generation with SafeGen

SafeGen is a meta-programming language for writing statically safe generators of Java programs. If a program generator written in SafeGen passes the checks of the SafeGen compiler, then the generator will only generate well-formed Java programs, for any generator input. In other words, statically checking the generator guarantees the correctness of any generated program, with respect to static checks commonly performed by a conventional compiler (including type safety, existence of a superclass, etc.). To achieve this guarantee, SafeGen supports only language primitives for reflection over an existing well-formed Java program, primitives for creating program fragments, and a restricted set of constructs for iteration, conditional actions, and name generation. SafeGen’s static checking algorithm is a combination of traditional type checking for Java, and a series of calls to a theorem prover to check the validity of first-order logical sentences constructed to represent well-formedness properties of the generated program under all inputs. The approach has worked quite well in our tests, providing proofs for correct generators or pointing out interesting bugs