Mining High Utility Itemsets with Hill Climbing and Simulated Annealing

High utility itemset mining (HUIM) is the task of finding all items set, purchased together, that generate a high profit in a transaction database. In the past, several algorithms have been developed to mine high utility itemsets (HUIs). However, most of them cannot properly handle the exponential search space while finding HUIs when the size of the database and total number of items increases. Recently, evolutionary and heuristic algorithms were designed to mine HUIs, which provided considerable performance improvement. However, they can still have a long runtime and some may miss many HUIs. To address this problem, this article proposes two algorithms for HUIM based on Hill Climbing (HUIM-HC) and Simulated Annealing (HUIM-SA). Both algorithms transform the input database into a bitmap for efficient utility computation and for search space pruning. To improve population diversity, HUIs discovered by evolution are used as target values for the next population instead of keeping the current optimal values in the next population. Through experiments on real-life datasets, it was found that the proposed algorithms are faster than state-of-the-art heuristic and evolutionary HUIM algorithms, that HUIM-SA discovers similar HUIs, and that HUIM-SA evolves linearly with the number of iterations.

Incremental Learning with Neural Network Algorithm for the Monitoring Pre-Convective Environments Using Geostationary Imager

Early warning of severe weather caused by intense convective weather systems is challenging. To help such activities, meteorological satellites with high temporal and spatial resolution have been utilized for the monitoring of instability trends along with water vapor variation. The current study proposes a retrieval algorithm based on an artificial neural network (ANN) model to quickly and efficiently derive total precipitable water (TPW) and convective available potential energy (CAPE) from Korea’s second geostationary satellite imagery measurements (GEO-KOMPSAT-2A/Advanced Meteorological Imager (AMI)). To overcome the limitations of the traditional static (ST) learning method such as exhaustive learning, impractical, and not matching in a sequence data, we applied an ANN model with incremental (INC) learning. The INC ANN uses a dynamic dataset that begins with the existing weight information transferred from a previously learned model when new samples emerge. To prevent sudden changes in the distribution of learning data, this method uses a sliding window that moves along the data with a window of a fixed size. Through an empirical test, the update cycle and the window size of the model are set to be one day and ten days, respectively. For the preparation of learning datasets, nine infrared brightness temperatures of AMI, six dual channel differences, temporal and geographic information, and a satellite zenith angle are used as input variables, and the TPW and CAPE from ECMWF model reanalysis (ERA5) data are used as the corresponding target values over the clear-sky conditions in the Northeast Asia region for about one year. Through the accuracy tests with radiosonde observation for one year, the INC NN results demonstrate improved performance (the accuracy of TPW and CAPE decreased by approximately 26% and 26% for bias and about 13% and 12% for RMSE, respectively) when compared to the ST learning. Evaluation results using ERA5 data also reveal more stable error statistics over time and overall reduced error distribution compared with ST ANN.

Mechanical Analysis and Corrosion Analysis of Zinc Alloys for Bioabsorbable Implants for Osteosynthesis

Zinc alloys have recently been researched intensely for their great properties as bioabsorbable implants for osteosynthesis. Pure zinc (Zn) itself has relatively poor strength, which makes it insufficient for most clinical use. Research has already proven that the mechanical strength of zinc can be enhanced significantly by alloying it with silver. This study evaluated zinc silver alloys (ZnAg) as well as novel zinc silver titanium alloys (ZnAgTi) regarding their mechanical properties for the use as bioabsorbable implants. Compared to pure zinc the mechanical strength was enhanced significantly for all tested zinc alloys. The elastic properties were only enhanced significantly for the zinc silver alloys ZnAg6 and ZnAg9. Regarding target values for orthopedic implants proposed in literature, the best mechanical properties were measured for the ZnAg3Ti1 alloy with an ultimate tensile strength of 262 MPa and an elongation at fracture of 16%. Besides the mechanical properties, the corrosion rates are important for bioabsorbable implants. This study tested the corrosion rates of zinc alloys in PBS solution (phosphate buffered solution) with electrochemical corrosion measurement. Zinc and its alloys showed favorable corrosion rates, especially in comparison to magnesium, which has a much lower degradation rate and no buildup of hydrogen gas pockets during the process. Altogether, this makes zinc alloys highly favorable for use as material for bioabsorbable implants for osteosynthesis.

Alleviation of Dyslipidemia via a Traditional Balanced Korean Diet Represented by a Low Glycemic and Low Cholesterol Diet in Obese Women in a Randomized Controlled Trial

A traditional balanced Korean diet (K-diet) may improve energy, glucose, and lipid metabolism. To evaluate this, we conducted a randomized crossover clinical trial, involving participants aged 30–40 years, who were randomly assigned to two groups—a K-diet or westernized Korean control diet daily, with an estimated energy requirement (EER) of 1900 kcal. After a 4-week washout period, they switched the diet and followed it for 4 weeks. The carbohydrate, protein, and fat ratios based on energy intake were close to the target values for the K-diet (65:15:20) and control diet (60:15:25). The glycemic index of the control diet and the K-diet was 50.3 ± 3.6 and 68.1 ± 2.9, respectively, and daily cholesterol contents in the control diet and K-diet were 280 and 150 mg, respectively. Anthropometric and biochemical parameters involved in energy, glucose, and lipid metabolism were measured while plasma metabolites were determined using UPLC-QTOF-MS before and after the 4-week intervention. After the four-week intervention, both diets improved anthropometric and biochemical variables, but the K-diet significantly reduced them compared to the control diet. Serum total cholesterol, non-high-density lipoprotein cholesterol, and triglyceride concentrations were significantly lower in the K-diet group than in the control diet group. The waist circumference (p = 0.108) and insulin resistance index (QUICKI, p = 0.089) tended to be lower in the K-diet group than in the control diet group. Plasma metabolites indicated that participants in the K-diet group tended to reduce insulin resistance compared to those in the control diet group. Amino acids, especially branched-chain amino acids, tyrosine, tryptophan, and glutamate, and L-homocysteine concentrations were considerably lower in the K-diet group than in the control diet group (p < 0.05). Plasma glutathione concentrations, an index of antioxidant status, and 3-hydroxybutyric acid concentrations, were higher in the K-diet group than in the control diet group. In conclusion, a K-diet with adequate calories to meet EER alleviated dyslipidemia by decreasing insulin resistance-related amino acids and increasing ketones in the circulation of obese women.

A Non-Invasive Method for Detection of Antihypertensive Drugs in Biological Fluids: The Salivary Therapeutic Drug Monitoring

Objectives: Arterial hypertension is still the most frequent cause of cardiovascular and cerebrovascular morbidity and mortality. Antihypertensive treatment has proved effective in reduction of cardiovascular risk. Nevertheless, lifestyle interventions and pharmacological therapy in some cases are ineffective in reaching blood pressure target values, despite full dose and poly-pharmacological treatment. Poor adherence to medications is an important cause of treatment failure. Different methods to assess therapeutic adherence are currently available: Therapeutic drug monitoring in biological fluids has previously demonstrated its efficacy and reliability. Plasma and urine have been already used for this purpose, but they may be affected by some practical limitations. Saliva may represent a feasible alternative.Methods: Fourteen antihypertensive drugs and two metabolites were simultaneously tested in plasma, urine, and saliva. Tested molecules included: atenolol, nebivolol, clonidine, ramipril, olmesartan, telmisartan, valsartan, amlodipine, nifedipine, doxazosin, chlorthalidone, hydrochlorothiazide, indapamide, sacubitril, ramiprilat, and sacubitrilat. Therapeutic drug monitoring was performed using ultra-high performance liquid chromatography, coupled to tandem mass spectrometry (UHPLC-MS/MS). The method has been preliminarily evaluated in a cohort of hypertensive patients.Results: The method has been validated according to US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidelines. The application on a cohort of 32 hypertensive patients has demonstrated sensibility and specificity of 98% and 98.1%, respectively, with a good feasibility in real-life clinical practice.Conclusion: Saliva may represent a feasible biological sample for therapeutic drug monitoring by non-invasive collection, prompt availability, and potential accessibility also in out-of-clinic settings.

An Extended Account of Trace-relating Compiler Correctness and Secure Compilation

Compiler correctness, in its simplest form, is defined as the inclusion of the set of traces of the compiled program in the set of traces of the original program. This is equivalent to the preservation of all trace properties. Here, traces collect, for instance, the externally observable events of each execution. However, this definition requires the set of traces of the source and target languages to be the same, which is not the case when the languages are far apart or when observations are fine-grained. To overcome this issue, we study a generalized compiler correctness definition, which uses source and target traces drawn from potentially different sets and connected by an arbitrary relation. We set out to understand what guarantees this generalized compiler correctness definition gives us when instantiated with a non-trivial relation on traces. When this trace relation is not equality, it is no longer possible to preserve the trace properties of the source program unchanged. Instead, we provide a generic characterization of the target trace property ensured by correctly compiling a program that satisfies a given source property, and dually, of the source trace property one is required to show to obtain a certain target property for the compiled code. We show that this view on compiler correctness can naturally account for undefined behavior, resource exhaustion, different source and target values, side channels, and various abstraction mismatches. Finally, we show that the same generalization also applies to many definitions of secure compilation, which characterize the protection of a compiled program linked against adversarial code.

Changes in methotrexate polyglutamate concentration in patients with rheumatoid arthritis during treatment and after discontinuation (review of two cases)

Introduction. The dynamics of changes in the concentration of polyglutamates of methotrexate (MTPG) over the past 20 years has been studied by several scientifc groups using various methods. For a number of reasons, the results of these studies cannot be called uniform and cannot be confdently projected onto the Russian population of patients with rheumatoid arthritis (RA). At the same time, therapeutic drug monitoring of methotrexate (MT) with clearly defned target values of metabolites could be an extremely useful tool in routine clinical practice.Purpose of the study. To characterize the concentration of MTPG in dynamics during treatment and 12 weeks after discontinuation of MT.Materials and methods. Two patients with early RA were traced 4, 12, 24 weeks after MT appointment, and also 12 weeks after its cancellation due to nausea that appeared during treatment. At each visit, an analysis was made for MTPG content by tandem gas chromatography-mass spectrometry.Results. Against the background of treatment, the signifcantly predominant metabolite was MTPG with three and gour residues of glutamic acid (the so-called long-chain), while 12 weeks after discontinuation, MTPG 2 was the predominant fraction.Conclusions. Low values of MTPG 3 and MTPG 4 with high values of MTPG 2 may indicate a recent initiation of treatment or MTB cancellation within the next 3 months. In the event of subjective adverse reactions (ADRs), it is advisable to consider the possibility of switching to a drug analogue of another manufacturer.

Determination of Heavy Metals in Soil around Amasoma Community in Bayelsa State, Nigeria

Aims: Anthropogenic activities such as crude oil exploration and exploitation has led to the suspicion of heavy metals contamination in the study area. This study investigated the concentration of zinc, nickel, lead and cadmium in the soil extracted from the area where Scent Leaf (Ocimum gratissimum) and Pawpaw tree (Carica papaya) are grown in Amassoma community, Bayelsa State, Nigeria. Study Design: Scent leaf (Ocimum gratissimum) and Pawpaw tree (Carica papaya) soils from where these plants are grown were randomly collected for heavy metal analysis from within Amassoma community in Southern Ijaw Local Government Area of Bayelsa State, Nigeria Place and Duration of Study: This study was carried out in Biological Sciences, Faculty of Science, Niger Delta University, Wilberforce Island, Amassoma, Bayelsa State between March 2019 to September 2019 Methodology: Scent leaf (Ocimum gratissimum) and Pawpaw tree (Carica papaya) soils were digested and analyzed for heavy metals using Atomic Absorption Spectrophotometer (AAS, model S471096). The method used was wet-ashing method for the analysis. Results: the concentrations of Lead (Pb), Nickel (Ni), Cadmium (Cd), and Zinc (Zn), in pawpaw soil and scent leaf soil. From the sample data analysis, the average lead (Pb) contents in pawpaw soil and scent leaf soil were 1.283 mg/kg and 1.44 mg/kg respectively. The average Cadmium (Cd) in pawpaw soil and scent leaf soil were 0.256 mg/kg and 0.256 mg/kg respectively. The average Nickel (Ni) compositions in pawpaw soil and scent leaf soil were 4.71 mg/kg and 5.09 mg/kg respectively. While the Average Zinc (Zn) in pawpaw soil and scent leaf soil is 2.280 mg/kg and 2.160 mg/kg respectively. The soil analyzed for heavy metals were below the threshold target values recommended by the WHO. Conclusion: The Scent leaf (Ocimum gratissimum) and Pawpaw tree (Carica papaya) soils analyzed for heavy metals were below the permissible limit recommended by WHO for soil safety. The result from the present study revealed that there may not be soil contamination as a result of the selected heavy metals, however, It is recommended that caution should be taken in regulating the anthropogenic activities that may tend to elevate the level of heavy metals in the surrounding to prevent contamination of soil over time which could be detrimental to the health of the populace.

Therapeutic drug monitoring of thiopurines: Effect of reduced 6-thioguanine nucleotide target levels in IBD patients

Aim: The effect of the Dutch nationwide adjustment of reduced 6-TGN target values (from 600-1200 pmol/8x108 RBC to 320-630 pmol/8x108 RBC) on toxicity and clinical outcome of thiopurine treatment in patients with inflammatory bowel disease (IBD) has not yet been established. Therefore the authors determined the incidence of toxicity-induced discontinuations and efficacy at both target concentrations. Methods: This retrospective study was performed in IBD patients treated with azathioprine or mercaptopurine. Two groups were defined: the former target (FT) group with target concentrations of 600-1200 pmol/8x10^8 RBC and the adjusted target (AT) group with target concentrations of 320-630 pmol/8x10^8 RBC. Patients were followed for maximum 52 weeks or until discontinuation of thiopurine therapy. Data were collected from the local hospital electronic health software of Rijnstate Hospital. Results: 151 patients were included, 76 in the FT group and 75 in the AT group. At week 52, 100 out of 150 patients (66%) of the total population discontinued thiopurine therapy. Forty-eight of this discontinuations were due toxicity (48%). The estimated cumulative incidence of toxicity was higher in the FT group compared to the AT group (47% and 35% respectively, p=0.25). No loss of efficacy was seen in the AT group. Conclusion: Reduction of the target range may lead to less toxicity induced discontinuations. In addition, this study did not find any indication that the reduction of the target range diminished efficacy.

Controllability of Fractional-Order Particle Swarm Optimizer and Its Application in the Classification of Heart Disease

This study proposes a method to improve fractional-order particle swarm optimizer to overcome the shortcomings of traditional swarm algorithms, such as low search accuracy in a high-dimensional space, falling into local minimums, and nonrobust results. In natural phenomena, our controllable fractional-order particle swarm optimizer can explore search spaces in detail to obtain high resolutions. Moreover, the proposed algorithm is memorable, i.e., position updates focus on the particle position of previous and last generations, rendering it conservative when updating the position, and obtained results are robust. For verifying the algorithm’s effectiveness, 11 test functions compare the average value, overall best value, and standard deviation of the controllable fractional-order particle swarm optimizer and controllable particle swarm optimizer; experimental results show that the stability of the former is better than the latter. Furthermore, the solution position found by the controllable fractional-order particle swarm optimizer is more reliable. Therefore, the improved method proposed herein is effective. Moreover, this research describes how a heart disease prediction application uses the optimizer we proposed to optimize XGBoost hyperparameters with custom target values. The final verification of the obtained prediction model is effective and reliable, which shows the controllability of our proposed fractional-order particle swarm optimizer.