Determination of volterra transfer functions of non-linear multiport networks

A method is presented to determine frequency domain Volterra transfer functions of non-linear multiport networks containing non-linear multiport subsystems (elements). the method is based on an extension of the probing method to allow arbitrary (also commensurate) frequencies. A recursively based algorithm for the determination of Volterra transfer functions of non-linear multiport networks is derived. A computer implementation of the method in a symbolic programming language is presented. This makes it possible to determine algebraic expressions of the Volterra transfer functions. Three examples are considered.     

Lipase-catalyzed esterification of lactic acid with straight-chain alcohols

Enzymatic synthesis of esters of lactic acid and straight-chain alcohols with different chain lengths (C₆–C₁₈) were investigated in batch reactions with hexadecanol (C₁₆) as the model alcohol. Cyclohexane was the best solvent for higher ester yields, and the best biocatalyst was the immobilized Candida antarctica lipase B (Novozym 435) as well as the textile-immobilized Candida sp. lipase. A method was established to obtain ester yields in the range of 71 to 82% for the different alcohols, and the most favorable conditions for the esterification reaction using Novozym 435 were an equimolar ratio of lactic acid to alcohol, each at a concentration of 120 mM each; a 50°C reaction temperature; 190 rpm shaking speed; and the addition of 100 mg molecular sieves (4 Å) for drying. The ester yield increased with increasing lipase load, and a yield of 79.2% could be obtained after 24 h of reaction at 20 wt% of Novozym 435. The immobilized Candida sp. lipase prepared in the laboratory also could be used to produce esters of lactic acid and straight-chain alcohols, but it had a much lower activity than Novozym 435 with a temperature optimum of 40°C.     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

Nutritional regulation of the activities of lipogenic enzymes of rat liver and brown adipose tissue

Nutrition-induced effects on the activity of enzymes of lipogenesis, fatty acid synthase (FAS: EC 2.3.1.85), ATP citrate lyase (ACL: EC 4.1.3.8), malic enzyme (ME; EC 1.1.1.40), glucose-6-phosphate dehydrogenase (G6PDH: EC 1.1.1.49) and 6-phosphogluconate dehydrogenase (PGDH; EC 1.1.1.44) were investigated in liver and interscapular brown adipose tissue (BAT) of rats. The lipogenic enzymes could be grouped into two categories according to their response to dietary manipulations: FAS and ACL, both key enzymes of lipogenesis, responded fast and strongly to dietary manipulations. ME, G6PDH and PGDH, enzymes which also contribute to metabolic pathways other than lipogenesis, responded in a more sustained and less pronounced fashion. Feed deprivation caused the specific activities of lipogenic enzymes to decline several-fold. Refeeding of previously fasted (up to 3 days) animals increased the activities dramatically (10-to 25-fold) to far above pre-fasting levels ("overshoot"). Repetition of the fasting/refeeding regimen increasingly impaired the ability of both tissues to synthesize overshooting enzyme activities in the subsequent refeeding period. The fasting-induced decline of the activities was prevented when sugars were provided to the animals via drinking water. The sugars displayed different effectivities: sucrose = glucose > fructose > maltose > > lactose. Sugars as the sole nutrient after fasting were also able to induce overshooting enzyme activities. Again, activities of FAS and ACL responded in a more pronounced fashion than the other three enzymes. Transition from feeding one diet to feeding a new diet of different composition led to adaptation of the lipogenic enzyme activities to levels characteristic for the new diet. Replacing a low-carbohydrate with a high-carbohydrate diet proceeded with major alterations of enzyme activities. This process of attaining a new level took up to 20 days and involved pronounced oscillations of the specific activities. In contrast, when a high-carbohydrate diet was replaced with another diet. particular one high in fat, transition to new enzyme activities was completed within 2-3 days and proceeded without oscillations. All dietary manipulations caused more pronounced responses in young (35d-old) than in adult (180d-old) animals.     

Linear-Time Self-Interpretation of the Pure Lambda Calculus

We show that linear-time self-interpretation of the pure untyped lambda calculus is possible, in the sense that interpretation has a constant overhead compared to direct execution under various execution models. The present paper shows this result for reduction to weak head normal form under call-by-name, call-by-value and call-by-need.We use a self-interpreter based on previous work on self-interpretation and partial evaluation of the pure untyped lambda calculus.We use operational semantics to define each reduction strategy. For each of these we show a simulation lemma that states that each inference step in the evaluation of a term by the operational semantics is simulated by a sequence of steps in evaluation of the self-interpreter applied to the term (using the same operational semantics).By assigning costs to the inference rules in the operational semantics, we can compare the cost of normal evaluation and self-interpretation. Three different cost-measures are used: number of beta-reductions, cost of a substitution-based implementation (similar to graph reduction) and cost of an environment-based implementation.For call-by-need we use a non-deterministic semantics, which simplifies the proof considerably.     

Casting traceability with direct part marking using reconfigurable pin-type tooling based on paraffin–graphite actuators

Green sand moulding machines for cast iron foundries are presently unable to uniquely identify individual castings. An insert tool concept is developed and tested via incremental mock-up development. The tool is part of the pattern plate and changes shape between each moulding, thus giving each mould a unique ID by embossing a Data Matrix symbol into the sand. In the process of producing the mould, each casting can be given a unique (DPM), enabling part tracking throughout the casting's life cycle. Sand embossing is achieved with paraffin-actuated reconfigurable pin-type tooling under simulated processing conditions. The marker geometry limitations have been tested using static symbol patterns, both for sand embossing and actual casting marking. The marked castings have successfully been identified with decoding software. The study shows that the function of each element of this technology can be successfully applied within the foundry industry.