Exploring Cognitive States: Methods for Detecting Physiological Temporal Fingerprints

Cognitive state detection and its relationship to observable physiologically telemetry has been utilized for many human-machine and human-cybernetic applications. This paper aims at understanding and addressing if there are unique psychophysiological patterns over time, a physiological temporal fingerprint, that is associated with specific cognitive states. This preliminary work involves commercial airline pilots completing experimental benchmark task inductions of three cognitive states: 1) Channelized Attention (CA); 2) High Workload (HW); and 3) Low Workload (LW). We approach this objective by modeling these "fingerprints" through the use of Hidden Markov Models and Entropy analysis to evaluate if the transitions over time are complex or rhythmic/predictable by nature. Our results indicate that cognitive states do have unique complexity of physiological sequences that are statistically different from other cognitive states. More specifically, CA has a significantly higher temporal psychophysiological complexity than HW and LW in EEG and ECG telemetry signals. With regards to respiration telemetry, CA has a lower temporal psychophysiological complexity than HW and LW. Through our preliminary work, addressing this unique underpinning can inform whether these underlying dynamics can be utilized to understand how humans transition between cognitive states and for improved detection of cognitive states

Phase I dose-escalation and pharmacokinetic study of dasatinib in patients with advanced solid tumors

PURPOSE: To determine the maximum tolerated dose, dose-limiting toxicity (DLT), and recommended phase II dose of dasatinib in metastatic solid tumors refractory to standard therapies or for which no effective standard therapy exists. <br></br> EXPERIMENTAL DESIGN: In this phase I, open-label, dose-escalation study, patients received 35 to 160 mg of dasatinib twice daily in 28-day cycles either every 12 hours for 5 consecutive days followed by 2 nontreatment days every week (5D2) or as continuous, twice-daily (CDD) dosing. <br></br> RESULTS: Sixty-seven patients were treated (5D2, n = 33; CDD, n = 34). The maximum tolerated doses were 120 mg twice daily 5D2 and 70 mg twice daily CDD. DLTs with 160 mg 5D2 were recurrent grade 2 rash, grade 3 lethargy, and one patient with both grade 3 prolonged bleeding time and grade 3 hypocalcemia; DLTs with 120 mg twice daily CDD were grade 3 nausea, grade 3 fatigue, and one patient with both grade 3 rash and grade 2 proteinuria. The most frequent treatment-related toxicities across all doses were nausea, fatigue, lethargy, anorexia, proteinuria, and diarrhea, with infrequent hematologic toxicities. Pharmacokinetic data indicated rapid absorption, dose proportionality, and lack of drug accumulation. Although no objective tumor responses were seen, durable stable disease was observed in 16% of patients.<br></br> CONCLUSION: Dasatinib was well tolerated in this population, with a safety profile similar to that observed previously in leukemia patients, although with much less hematologic toxicity. Limited, although encouraging, preliminary evidence of clinical activity was observed. Doses of 120 mg twice daily (5D2) or 70 mg twice daily (CDD) are recommended for further studies in patients with solid tumors.<br></br&gt

Diversity analysis of Sweet Potato (Ipomoea batatas[L.] Lam) genotypes using morphological, biochemical and molecular markers

276-285Sweet potato [Ipomeabatatas(L.) Lam.]is a nutritious food crop primarily grown by small and marginal farmers. Successful breeding and germplasm conservation programs demands characterization of its germplasm. Here, we tried to determine genetic diversity among 21 sweet potato genotypes using morphological, biochemical and molecular markers. Ten morphological traits were studied and subjected to analysis of variance (ANOVA). Mean square due to germplasm were highly significant as well as wide mean range performance was observed for tuber number per plant, individual tuber weight, tuber fresh yield per plant, tuber dry yield per plant, tuber yield per plot and tuber length. UPGMA (Unweighted Pair Group Method Arithmetic Average) cluster analysis based on morphological traits separated the germplasm into three groups. The genotypes Gautam, Shree Arun, RS-92 and CO-3-4 appeared promising with regard to yield characters. Total phenol was maximum in in V-12 genotype (1.39 mg), while minimum was recorded in Samrat genotype (0.95 mg). The highest total antioxidant was observed in the genotype Samrat (0.30 mg), while minimum was recorded in the genotype Navsari Local (0.16 mg). Molecular diversity analysis was carried out using 25 RAPD (Random Amplified Polymorphic DNA) primers, out of which 13 primers produced 117 reproducible amplicons (106 polymorphic, 7 monomorphic and 4 unique amplicons). UPGMA dendogram based on RAPD data separated the genotypes into two major clusters having the similarity coefficient ranged from 0.56 to 0.76. The results can be used for sweet potato crop improvement through molecular breeding and marker assisted selection of for desired traits in future

POLAROGRAPHIC STUDIES OF As (III) AND Sb(III) WITH SERINE

ABSTRACT The reduction of As(III) and Sb(III) with serine is investigated polarographically in aqueous medium. As(III) and Sb(III) formed 1:1, 1:2 and 1:3 complex species with Serine. The stability constants of As(III) and Sb(III) with serine were evaluated by the method of DeFord and Hume. The reduction of the system in each case is quasireversible and diffusion controlled, involving three electrons. The thermodynamic parameters have been determined. The stability constants of these species at 300K for As(III) with serine are logβ 1 = 2.17, logβ 2 = 4.60, logβ 3 = 6.73 and at 310 K are logβ 1 = 1.87, logβ 2 = 4.00, logβ 3 = 6.55 and thermodynamic parameters free energy (KCal mo

IMECE2008-66998 FAILURE OF THREE CEMENTLESS MODULAR TOTAL HIP ARTHROPLASTY PROSTHESES: A RETRIEVAL ANALYSIS

ABSTRACT The reasons leading to the in vivo failure of three titanium alloy modular implants in cementless total hip arthroplasty were investigated. The implantation period ranged from 18 months to over three years. Two were fractured in vivo and the other was retrieved secondary to aseptic loosening after 18 months in service. Macroscopic examination showed close topographical similarities between the two fractured implants. Dark elliptical striations on the fractured site indicated the occurrence of low cycle fatigue. Light Microscopy and Scanning Electron Microscopy confirmed the presence of fretting, pitting, plastic deformation, and stress-induced corrosion cracking. In two of the three implants, EDS confirmed metal ion traces in the tissue around the implant. However, nothing unusual was found in the third unfractured implant. Taper performance is influenced by metallurgy, the load carried and the effect of the local microenvironment. Methods to reduce the impact of these factors may reduce the incidence of taper related failure

IMECE2008-67967 EVALUATION OF THE EFFECT OF CEMENT VISCOSITY ON CEMENT MANTLE IN TOTAL KNEE ARTHROPLASTY

ABSTRACT Aseptic loosening of the tibial implant remains one of the major reasons of failure in Total Knee Arthroplasty (TKA). The cement viscosity at the time of application to the bone is of grea

Development of a fuzzy logic-based solar charge controller for charging lead-acid batteries

Este documento se considera que es una ponencia de congresos en lugar de un artículo.International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2019), Oct. 28-31 2019, Ambato (Ecuador)The design and implementation of a solar charge controller for lead-acid batteries is intended to supplement a component of the water purification module of the water treatment unit for natural disaster relief. This unit contains a solar panel system that supplies power to the module by charging batteries through a controller comprising an Atmega 328 processor. The solar panel feeds voltage to the batteries through fuzzy logic-based software, which allows up to 6 A DC to pass through the controller's power circuit. Consequently, the battery was charged in less time (an average of 7 h to reach maximum capacity), wherein battery lifespan is related to the charge wave frequency. Thus, our software may be adapted in different control algorithms without having to change hardware

Characterizing and mapping cropping patterns in a complex agro-ecosystem: An iterative participatory mapping procedure using machine learning algorithms and MODIS vegetation indices

Accurate and up-to-date spatial agricultural information is essential for applications including agro-environmental assessment, crop management, and appropriate targeting of agricultural technologies. There is growing research interest in spatial analysis of agricultural ecosystems applying satellite remote sensing technologies. However, usability of information generated from many of remotely sensed data is often constrained by accuracy problems. This is of particular concern in mapping complex agro-ecosystems in countries where small farm holdings are dominated by diverse crop types. This study is a contribution to the ongoing efforts towards overcoming accuracy challenges faced in remote sensing of agricultural ecosystems. We applied time-series analysis of vegetation indices (Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) derived from the Moderate Resolution Imaging Spectrometer (MODIS) sensor to detect seasonal patterns of irrigated and rainfed cropping patterns in five townships in the Central Dry Zone of Myanmar, which is an important agricultural region of the country has been poorly mapped with respect to cropping practices. To improve mapping accuracy and map legend completeness, we implemented a combination of (i) an iterative participatory approach to field data collection and classification, (ii) the identification of appropriate size and types of predictor variables (VIs), and (iii) evaluation of the suitability of three Machine Learning algorithms: Support Vector Machine (SVM), Random Forest (RF), and C5.0 algorithms under varying training sample sizes. Through these procedures, we were able to progressively improve accuracy and achieve maximum overall accuracy of 95% When a small sized training dataset was used, accuracy achieved by RF was significantly higher compared to SVM and C5.0 (P < 0.01), but as sample size increased, accuracy differences among the three machine learning algorithms diminished. Accuracy achieved by use of NDVI was consistently better than that of EVI (P < 0.01). The maximum overall accuracy was achieved using RF and 8-days NDVI composites for three years of remote sensing data. In conclusion, our findings highlight the important role of participatory classification, especially in areas where cropping systems are highly diverse and differ over space and time. We also show that the choice of classifiers and size of predictor variables are essential and complementary to the participatory mapping approach in achieving desired accuracy of cropping pattern mapping in areas where other sources of spatial information are scarce