Fourier self-deconvolution in coherent anti-Stokes Raman scattering spectrum analysis

Coherent anti-Stokes Raman scattering (CARS) microscopy is rapidly developing into a unique microscopic tool in biophysics, biology and the material sciences. The nonlinear nature of CARS spectroscopy complicates the analysis of the received spectra. There were developed mathematical methods for signal processing and for calculations spectra. Fourier self-deconvolution is a special high pass FFT filter which synthetically narrows the effective trace bandwidth features. As Fourier self-deconvolution can effectively reduce the noise, which may be at a higher spatial frequency than the peaks, without losing peak resolution. The idea of the work is to experiment the possibility of using wavelet decomposition in spectroscopic for background and noise removal, and Fourier transformation for linenarrowing.

Retrieval of kinetic rates in reactions with semi batch liquid phase using ill-posed inverse problem theory

A neural network procedure to solve inverse chemical kinetic problems is discussed in this work. Rate constants are calculated from the product concentration of an irreversible consecutive reaction: the hydrogenation of Citral molecule, a process with industrial interest. Simulated and experimental data are considered. Errors in the simulated data, up to 7% in the concentrations, were assumed to investigate the robustness of the inverse procedure. Also, the proposed method is compared with two common methods in nonlinear analysis; the Simplex and Levenberg-Marquardt approaches. In all situations investigated, the neural network approach was numerically stable and robust with respect to deviations in the initial conditions or experimental noises.

Methane combustion kinetic rate constants determination: an ill-posed inverse problem analysis

Methane combustion was studied by the Westbrook and Dryer model. This well-established simplified mechanism is very useful in combustion science, for computational effort can be notably reduced. In the inversion procedure to be studied, rate constants are obtained from [CO] concentration data. However, when inherent experimental errors in chemical concentrations are considered, an ill-conditioned inverse problem must be solved for which appropriate mathematical algorithms are needed. A recurrent neural network was chosen due to its numerical stability and robustness. The proposed methodology was compared against Simplex and Levenberg-Marquardt, the most used methods for optimization problems.

Effects of interband and intraband impurity scattering on coherence length in the pnictide superconductors

After discovery of cuprates, a search for new high temperature superconducting families began and it led to the discovery of layered pnictide compounds with critical temperatures limited up to ∼56 K. Pnictides consist elements from Group V of Periodic Table (nitrogen, phosphorus, arsenic, antimony and bismuth). In this work coherence length h in mixed state of pnictide superconductors is calculated numerically. In calculation is taken into account interband and intraband impurity scattering in framework of quasiclassical Eilenberger theory for s± pairing symmetry. Differences between Ginzburg-Landau and Eilenberger theories is shown and the comparison with existing models is done.

Effects of interband and intraband impurity scattering on coherence length in the pnictide superconductors

After discovery of cuprates, a search for new high temperature superconducting families began and it led to the discovery of layered pnictide compounds with critical temperatures limited up to ~56 K. Pnictides consist elements from Group V of Periodic Table (nitrogen, phosphorus, arsenic, antimony and bismuth). In this work coherence length ξh in mixed state of pnictide superconductors is calculated numerically. In calculation is taken into account interband and intraband impurity scattering in framework of quasiclassical Eilenberger theory for s± pairing symmetry. Differences between Ginzburg-Landau and Eilenberger theories is shown and the comparison with existing models is done.

Compton scattering tomography for agricultural measurements

This paper presents a new approach in tomographic instrumentation for agriculture based on Compton scattering, which allows for the simultaneous measurements of density and moisture of soil samples. Compton tomography is a technique that can be used to obtain a spatial map of electronic density of samples. Quantitative results can be obtained by using a reconstruction algorithm that takes into account the absorption of incident and scattered radiation. Results show a coefficient of linear correlation better than 0.81, when comparison is made between soil density measurements based on this method and direct transmission tomography. For soil water contents, a coefficient of linear correlation better than 0.79 was found when compared with measurements obtained by time domain reflectrometry (TDR). In addition, a set of Compton scatter images are presented to illustrate the efficacy of this imaging technique, which makes possible improved spatial variability analysis of pre-established planes.

Business intelligence viewpoint on managerial decision-making : Ill-structured problems and decision support systems

Vaikka liiketoimintatiedon hallintaa sekä johdon päätöksentekoa on tutkittu laajasti, näiden kahden käsitteen yhteisvaikutuksesta on olemassa hyvin rajallinen määrä tutkimustietoa. Tulevaisuudessa aiheen tärkeys korostuu, sillä olemassa olevan datan määrä kasvaa jatkuvasti. Yritykset tarvitsevat jatkossa yhä enemmän kyvykkyyksiä sekä resursseja, jotta sekä strukturoitua että strukturoimatonta tietoa voidaan hyödyntää lähteestä riippumatta. Nykyiset Business Intelligence -ratkaisut mahdollistavat tehokkaan liiketoimintatiedon hallinnan osana johdon päätöksentekoa. Aiemman kirjallisuuden pohjalta, tutkimuksen empiirinen osuus tunnistaa liiketoimintatiedon hyödyntämiseen liittyviä tekijöitä, jotka joko tukevat tai rajoittavat johdon päätöksentekoprosessia. Tutkimuksen teoreettinen osuus johdattaa lukijan tutkimusaiheeseen kirjallisuuskatsauksen avulla. Keskeisimmät tutkimukseen liittyvät käsitteet, kuten Business Intelligence ja johdon päätöksenteko, esitetään relevantin kirjallisuuden avulla – tämän lisäksi myös dataan liittyvät käsitteet analysoidaan tarkasti. Tutkimuksen empiirinen osuus rakentuu tutkimusteorian pohjalta. Tutkimuksen empiirisessä osuudessa paneudutaan tutkimusteemoihin käytännön esimerkein: kolmen tapaustutkimuksen avulla tutkitaan sekä kuvataan toisistaan irrallisia tapauksia. Jokainen tapaus kuvataan sekä analysoidaan teoriaan perustuvien väitteiden avulla – nämä väitteet ovat perusedellytyksiä menestyksekkäälle liiketoimintatiedon hyödyntämiseen perustuvalle päätöksenteolle. Tapaustutkimusten avulla alkuperäistä tutkimusongelmaa voidaan analysoida tarkasti huomioiden jo olemassa oleva tutkimustieto. Analyysin tulosten avulla myös yksittäisiä rajoitteita sekä mahdollistavia tekijöitä voidaan analysoida. Tulokset osoittavat, että rajoitteilla on vahvasti negatiivinen vaikutus päätöksentekoprosessin onnistumiseen. Toisaalta yritysjohto on tietoinen liiketoimintatiedon hallintaan liittyvistä positiivisista seurauksista, vaikka kaikkia mahdollisuuksia ei olisikaan hyödynnetty. Tutkimuksen merkittävin tulos esittelee viitekehyksen, jonka puitteissa johdon päätöksentekoprosesseja voidaan arvioida sekä analysoida. Despite the fact that the literature on Business Intelligence and managerial decision-making is extensive, relatively little effort has been made to research the relationship between them. This particular field of study has become important since the amount of data in the world is growing every second. Companies require capabilities and resources in order to utilize structured data and unstructured data from internal and external data sources. However, the present Business Intelligence technologies enable managers to utilize data effectively in decision-making. Based on the prior literature, the empirical part of the thesis identifies the enablers and constraints in computer-aided managerial decision-making process. In this thesis, the theoretical part provides a preliminary understanding about the research area through a literature review. The key concepts such as Business Intelligence and managerial decision-making are explored by reviewing the relevant literature. Additionally, different data sources as well as data forms are analyzed in further detail. All key concepts are taken into account when the empirical part is carried out. The empirical part obtains an understanding of the real world situation when it comes to the themes that were covered in the theoretical part. Three selected case companies are analyzed through those statements, which are considered as critical prerequisites for successful computer-aided managerial decision-making. The case study analysis, which is a part of the empirical part, enables the researcher to examine the relationship between Business Intelligence and managerial decision-making. Based on the findings of the case study analysis, the researcher identifies the enablers and constraints through the case study interviews. The findings indicate that the constraints have a highly negative influence on the decision-making process. In addition, the managers are aware of the positive implications that Business Intelligence has for decision-making, but all possibilities are not yet utilized. As a main result of this study, a data-driven framework for managerial decision-making is introduced. This framework can be used when the managerial decision-making processes are evaluated and analyzed.

Hypomagnesemia in critically ill cancer patients: a prospective study of predictive factors

Hypomagnesemia is the most common electrolyte disturbance seen upon admission to the intensive care unit (ICU). Reliable predictors of its occurrence are not described. The objective of this prospective study was to determine factors predictive of hypomagnesemia upon admission to the ICU. In a single tertiary cancer center, 226 patients with different diagnoses upon entering were studied. Hypomagnesemia was defined by serum levels <1.5 mg/dl. Demographic data, type of cancer, cause of admission, previous history of arrhythmia, cardiovascular disease, renal failure, drug administration (particularly diuretics, antiarrhythmics, chemotherapy and platinum compounds), previous nutrition intake and presence of hypovolemia were recorded for each patient. Blood was collected for determination of serum magnesium, potassium, sodium, calcium, phosphorus, blood urea nitrogen and creatinine levels. Upon admission, 103 (45.6%) patients had hypomagnesemia and 123 (54.4%) had normomagnesemia. A normal dietary habit prior to ICU admission was associated with normal Mg levels (P = 0.007) and higher average levels of serum Mg (P = 0.002). Postoperative patients (N = 182) had lower levels of serum Mg (0.60 ± 0.14 mmol/l compared with 0.66 ± 0.17 mmol/l, P = 0.006). A stepwise multiple linear regression disclosed that only normal dietary habits (OR = 0.45; CI = 0.26-0.79) and the fact of being a postoperative patient (OR = 2.42; CI = 1.17-4.98) were significantly correlated with serum Mg levels (overall model probability = 0.001). These findings should be used to identify patients at risk for such disturbance, even in other critically ill populations.

Clinical utility of standard base excess in the diagnosis and interpretation of metabolic acidosis in critically ill patients

The aims of this study were to determine whether standard base excess (SBE) is a useful diagnostic tool for metabolic acidosis, whether metabolic acidosis is clinically relevant in daily evaluation of critically ill patients, and to identify the most robust acid-base determinants of SBE. Thirty-one critically ill patients were enrolled. Arterial blood samples were drawn at admission and 24 h later. SBE, as calculated by Van Slyke's (SBE VS) or Wooten's (SBE W) equations, accurately diagnosed metabolic acidosis (AUC = 0.867, 95%CI = 0.690-1.043 and AUC = 0.817, 95%CI = 0.634-0.999, respectively). SBE VS was weakly correlated with total SOFA (r = -0.454, P < 0.001) and was similar to SBE W (r = -0.482, P < 0.001). All acid-base variables were categorized as SBE VS <-2 mEq/L or SBE VS <-5 mEq/L. SBE VS <-2 mEq/L was better able to identify strong ion gap acidosis than SBE VS <-5 mEq/L; there were no significant differences regarding other variables. To demonstrate unmeasured anions, anion gap (AG) corrected for albumin (AG A) was superior to AG corrected for albumin and phosphate (AG A+P) when strong ion gap was used as the standard method. Mathematical modeling showed that albumin level, apparent strong ion difference, AG A, and lactate concentration explained SBE VS variations with an R² = 0.954. SBE VS with a cut-off value of <-2 mEq/L was the best tool to diagnose clinically relevant metabolic acidosis. To analyze the components of SBE VS shifts at the bedside, AG A, apparent strong ion difference, albumin level, and lactate concentration are easily measurable variables that best represent the partitioning of acid-base derangements.

Outcomes and organ dysfunctions of critically ill patients with systemic lupus erythematosus and other systemic rheumatic diseases

Our objective was to compare the pattern of organ dysfunctions and outcomes of critically ill patients with systemic lupus erythematosus (SLE) with patients with other systemic rheumatic diseases (SRD). We studied 116 critically ill SRD patients, 59 SLE and 57 other-SRD patients. The SLE group was younger and included more women. Respiratory failure (61%) and shock (39%) were the most common causes of ICU admission for other-SRD and SLE groups, respectively. ICU length-of-stay was similar for the two groups. The 60-day survival adjusted for the groups’ baseline imbalances was not different (P = 0.792). Total SOFA scores were equal for the two groups at admission and during ICU stay, although respiratory function was worse in the other-SRD group at admission and renal and hematological functions were worse in the SLE group at admission. The incidence of severe respiratory dysfunction (respiratory SOFA >2) at admission was higher in the other-SRD group, whereas severe hematological dysfunction (hematological SOFA >2) during ICU stay was higher in the SLE group. SLE patients were younger and displayed a decreased incidence of respiratory failure compared to patients with other-SRDs. However, the incidences of renal and hematological failure and the presence of shock at admission were higher in the SLE group. The 60-day survival rates were similar.

Furosemide is associated with acute kidney injury in critically ill patients

Acute kidney injury (AKI) is common in critically ill patients. Diuretics are used without any evidence demonstrating a beneficial effect on renal function. The objective of the present study is to determine the incidence of AKI in an intensive care unit (ICU) and if there is an association between the use of furosemide and the development of AKI. The study involved a hospital cohort in which 344 patients were consecutively enrolled from January 2010 to January 2011. A total of 132 patients (75 females and 57 males, average age 64 years) remained for analysis. Most exclusions were related to ICU discharge in the first 24 h. Laboratory, sociodemographic and clinical data were collected until the development of AKI, medical discharge or patient death. The incidence of AKI was 55% (95%CI = 46-64). The predictors of AKI found by univariate analysis were septic shock: OR = 3.12, 95%CI = 1.36-7.14; use of furosemide: OR = 3.27, 95%CI = 1.57-6.80, and age: OR = 1.02 (95%CI = 1.00-1.04). Analysis of the subgroup of patients with septic shock showed that the odds ratio of furosemide was 5.5 (95%CI = 1.16-26.02) for development of AKI. Age, use of furosemide, and septic shock were predictors of AKI in critically ill patients. Use of furosemide in the subgroup of patients with sepsis/septic shock increased (68.4%) the chance of development of AKI when compared to the sample as a whole (43.9%).

Effect of heat and moisture exchangers on the prevention of ventilator-associated pneumonia in critically ill patients

Ventilator-associated pneumonia (VAP) remains one of the major causes of infection in the intensive care unit (ICU) and is associated with the length of hospital stay, duration of mechanical ventilation, and use of broad-spectrum antibiotics. We compared the frequency of VAP 10 months prior to (pre-intervention group) and 13 months after (post-intervention group) initiation of the use of a heat and moisture exchanger (HME) filter. This is a study with prospective before-and-after design performed in the ICU in a tertiary university hospital. Three hundred and fourteen patients were admitted to the ICU under mechanical ventilation, 168 of whom were included in group HH (heated humidifier) and 146 in group HME. The frequency of VAP per 1000 ventilator-days was similar for both the HH and HME groups (18.7 vs 17.4, respectively; P = 0.97). Duration of mechanical ventilation (11 vs 12 days, respectively; P = 0.48) and length of ICU stay (11 vs 12 days, respectively; P = 0.39) did not differ between the HH and HME groups. The chance of developing VAP was higher in patients with a longer ICU stay and longer duration of mechanical ventilation. This finding was similar when adjusted for the use of HME. The use of HME in intensive care did not reduce the incidence of VAP, the duration of mechanical ventilation, or the length of stay in the ICU in the study population.

Application of a modified sequential organ failure assessment score to critically ill patients

The purpose of the present study was to explore the usefulness of the Mexican sequential organ failure assessment (MEXSOFA) score for assessing the risk of mortality for critically ill patients in the ICU. A total of 232 consecutive patients admitted to an ICU were included in the study. The MEXSOFA was calculated using the original SOFA scoring system with two modifications: the PaO2/FiO2 ratio was replaced with the SpO2/FiO2 ratio, and the evaluation of neurologic dysfunction was excluded. The ICU mortality rate was 20.2%. Patients with an initial MEXSOFA score of 9 points or less calculated during the first 24 h after admission to the ICU had a mortality rate of 14.8%, while those with an initial MEXSOFA score of 10 points or more had a mortality rate of 40%. The MEXSOFA score at 48 h was also associated with mortality: patients with a score of 9 points or less had a mortality rate of 14.1%, while those with a score of 10 points or more had a mortality rate of 50%. In a multivariate analysis, only the MEXSOFA score at 48 h was an independent predictor for in-ICU death with an OR = 1.35 (95%CI = 1.14-1.59, P < 0.001). The SOFA and MEXSOFA scores calculated 24 h after admission to the ICU demonstrated a good level of discrimination for predicting the in-ICU mortality risk in critically ill patients. The MEXSOFA score at 48 h was an independent predictor of death; with each 1-point increase, the odds of death increased by 35%.