Treatment of schizophrenic psychoses with Lyorodin

Forty-four patients suffering from acute and chronic schizophrenic psychoses were used to obtain, by using Lorr's scale (IMPS) and taking the changes in disease state observed within three months as a base, suggestions or pointers as to the proper treatment of disease with fluphenazine (lyorodin) which is a neuroleptically highly potent phenothiazine derivative. Megalomania, grandiose delusions apathetic and depressive syndromes showed marked tendencies toward major improvement. An "antiautistic" effect was observed in chronic patients. The effective dose was between 6 and 12 mg a day. The drug was well tolerated. In the majority of cases it was also necessary for antiparkinsonian drugs to be administered to patients. After twelve months of treatment, slight to major improvements or even freedom from symptoms could be observed in 28 cases (or 64%).     

CIOs must look beyond the IS horizon

Executives in healthcare have traditionally had a difficult time communicating with their information managers, believing that they themselves must be technically oriented to understand their own IS system. The author argues that it is the chief information officers who must deepen their knowledge of the industry they have decided to pursue. This in turn will help them become more valuable members of the top executive team as it formulates strategic plans.     

Determinants of temperature in small coastal embayments of Lake Ontario

Along 25 km of the Lake Ontario shoreline near Toronto, Ontario, small coastal embayments (0.4–32 ha) have been constructed or modified by lake-infilling to restore warmwater fish habitat. The variation in thermal habitat quality for warmwater fishes among these embayments is very high; temperatures range from those found within a small pond to those of much cooler Lake Ontario. Since meteorological conditions and surface heat fluxes are almost identical, the temperature variation among embayments must be caused by differences in bathymetry or exchange with Lake Ontario. However, a previous study on these embayments found paradoxically that temperatures were not strongly associated with channel size or embayment bathymetry. This paper resolves the paradox by showing that flushing times for almost all of the constructed embayments were less than 1 day, and often less than 12 h. With so little time to warm within the embayments, water temperatures of almost all embayments remained very close to the temperatures of the adjacent lake waters. The coldest embayments connected directly to open Lake Ontario and warmer embayments connected to Lake Ontario through other embayments or protected harbors, where the inflowing water from Lake Ontario had already substantially warmed. To allow embayments along the exposed shoreline of Toronto to reach acceptable temperatures for warmwater fish, we use heat budgets to calculate that average summer flushing times must be increased from their current length of 1.5 to 5.5 h to approximately 30 h. Such changes could be achieved through large reductions in the channel cross section.     

Improved generative semisupervised learning based on finely grained component-conditional class labeling

We introduce new inductive, generative semisupervised mixtures with more finely grained class label generation mechanisms than in previous work. Our models combine advantages of semisupervised mixtures, which achieve label extrapolation over a component, and nearest-neighbor (NN)/nearest-prototype (NP) classification, which achieve accurate classification in the vicinity of labeled samples or prototypes. For our NN-based method, we propose a novel two-stage stochastic data generation, with all samples first generated using a standard finite mixture and then all class labels generated, conditioned on the samples and their components of origin. This mechanism entails an underlying Markov random field, specific to each mixture component or cluster. We invoke the pseudo-likelihood formulation, which forms the basis for an approximate generalized expectation-maximization model learning algorithm. Our NP-based model overcomes a problem with the NN-based model that manifests at very low labeled fractions. Both models are advantageous when within-component class proportions are not constant over the feature space region "owned by" a component. The practicality of this scenario is borne out by experiments on UC Irvine data sets, which demonstrate significant gains in classification accuracy over previous semisupervised mixtures and also overall gains, over KNN classification. Moreover, for very small labeled fractions, our methods overall outperform supervised linear and nonlinear kernel support vector machines.     

Hybrid method for designing digital Butterworth filters

A procedure for designing digital Butterworth filters is proposed. The procedure determines the denominator and the numerator of the filter transfer function based on the positions of the poles in the s-plane and zeros in the z-plane, respectively, and calculates the gain factor using a maximum point normalization method. In contrast to some conventional algorithms, the presented procedure is much simpler by directly obtaining the filter with 3-dB frequencies. This makes the presented algorithm a useful tool for determining the boundaries in electronic or communication systems’ frequency responses. Moreover, the proposed algorithm is compatible with high-order transformations which are the limitations of general pole-zero placement techniques. The proposed method is illustrated by the examples of designing the low-pass, high-pass, band-pass, and band-stop filter.     

The influence of skin depth on crack measurement by the ac field technique

A general solution is given to describe the ac field around surface-breaking cracks for arbitrary values of the ratio of skin depth δ to crack depthd. This solution allows accurate interpretation of crack depth from voltage readings taken by a Crack Microgauge instrument in cases where δ andd are comparable. It is shown to agree with asymptotic formulae obtained for the cases where δ/d is very small and very large. Provided that the probe length Δ is large compared with δ, the calculations show that a very good approximation to the crack depth may be obtained, irrespective of the ratio δ/d, by using the thin-skin asymptotic formula $$d = \frac{1}{2}\Delta (V_2 - V_1 )/V_1 $$ whereV ₁ andV ₂ are probe voltages registered at positions just off and across the crack, respectively. The problem is solved for a crack of infinite aspect ratio which has no opening, but it can be applied with confidence at the centerline of cracks of fairly large aspect ratio.     

The Morning After: Limit Violations and the Self-Regulation of Alcohol Consumption.

The authors examined whether the reciprocal relationship between alcohol consumption and distress unfolded over time in 2 samples of social drinkers. Participants monitored their alcohol intake and their cognitive and emotional responses to that drinking on hand-held computers. On mornings after drinking, those who had violated their self-imposed limits the day before reported more guilt, even after controlling for acute negative symptoms of drinking and amount consumed. Reciprocally, guilt led to poorer self-regulation of alcohol intake: Greater distress over alcohol consumption was linked to more intake, intoxication, and more limit violations. Individual differences moderated the relationships among limit violations, distress, and drinking. Consistent with the limit violation effect, violating a limit produced distress over consumption among social drinkers, and they responded to that distress by drinking more. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fuzzy PI control design for an industrial weigh belt feeder

An industrial weigh belt feeder is used to transport solid materials into a manufacturing process at a constant feedrate. It exhibits nonlinear behavior because of motor friction, saturation, and quantization noise in the sensors, which makes standard autotuning methods difficult to implement. The paper proposes and experimentally demonstrates two types of fuzzy logic controllers for an industrial weigh belt feeder. The first type is a PI-like fuzzy logic controller (FLC). A gain scheduled PI-like FLC and a self-tuning PI-like FLC are presented. For the gain scheduled PI-like FLC the output scaling factor of the controller is gain scheduled with the change of setpoint. For the self-tuning PI-like FLC, the output scaling factor of the controller is modified online by an updating factor whose value is determined by a rule base with the error and change of error of the controlled variable as the inputs. A fuzzy PI controller is also presented, where the proportional and integral gains are tuned online based on fuzzy inference rules. Experimental results show the effectiveness of the proposed fuzzy logic controllers. A performance comparison of the three controllers is also given.