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This study was designed to improve blood glucose level predictability and future hypoglycemic and hyperglycemic event alerts through a novel patient-specific supervised-machine-learning (SML) analysis of glucose level based on a continuous-glucose-monitoring system (CGM) that needs no human intervention, and minimises false-positive alerts. The CGM data over 7 to 50 non-consecutive days from 11 type-1 diabetic patients aged 18 to 39 with a mean HbA1C of 7.5% ± 1.2% were analysed using four SML models. The algorithm was constructed to choose the best-fit model for each patient. Several statistical parameters were calculated to aggregate the magnitudes of the prediction errors. The personalised solutions provided by the algorithm were effective in predicting glucose levels 30 minutes after the last measurement. The average root-mean-square-error was 20.48 mg/dL and the average absolute-mean-error was 15.36 mg/dL when the best-fit model was selected for each patient. Using the best-fit-model, the true-positive-hypoglycemia-prediction-rate was 64%, whereas the false-positive- rate was 4.0%, and the false-negative-rate was 0.015%. Similar results were found even when only CGM samples below 70 were considered. The true-positive-hyperglycemia-prediction-rate was 61%. State-of-the-art SML tools are effective in predicting the glucose level values of patients with type-1diabetes and notifying these patients of future hypoglycemic and hyperglycemic events, thus improving glycemic control. The algorithm can be used to improve the calculation of the basal insulin rate and bolus insulin, and suitable for a closed loop "artificial pancreas" system. The algorithm provides a personalised medical solution that can successfully identify the best-fit method for each patient., (© 2020 John Wiley & Sons Ltd.)

The problem for pricing the Israel option with time-changed compensation was studied based on the high-order recombined multinomial tree by using a fast Fourier transform to approximate a Lévy process. First, the Lévy option pricing model and Fourier transform are introduced. Then, a network model based on FFT (Markov chain) is presented. After that, an FFT-based multinomial tree construction method is given to solve the problem of difficult parameter estimation when approximating the Lévy process with high-order multinomial trees. It is proved that the discrete random variables corresponding to the multinomial tree converge to the Lévy-distributed continuous random variable. Next, an algorithm based on a reverse recursion algorithm for pricing the Israel option with time-changed compensation was presented. Finally, an example was illustrated, and the relationship between the price of the Israel option and the time-changed compensation was discussed. The results show that the method of constructing a high-order recombined multinomial tree based on FFT has very high calculation precision and calculation speed, which can solve the problem of traditional risk-neutral multinomial tree construction, and it is a promising pricing method for pricing Israel options., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Weiwei Wang and Xiaoping Hu.)

Voting is an essential mechanism that allows multiple agents to reach a joint decision. The joint decision, representing a function over the preferences of all agents, is the winner among all possible (candidate) decisions. To compute the winning candidate, previous work has typically assumed that voters send their complete set of preferences for computation, and in fact this has been shown to be required in the worst case. However, in practice, it may be infeasible for all agents to send a complete set of preferences due to communication limitations and willingness to keep as much information private as possible. The goal of this paper is to empirically evaluate algorithms to reduce communication on various sets of experiments. Accordingly, we propose an iterative algorithm that allows the agents to send only part of their preferences, incrementally. Experiments with simulated and real-world data show that this algorithm results in an average of 35% savings in communications, while guaranteeing that the actual winning candidate is revealed. A second algorithm applies a greedy heuristic to save up to 90% of communications. While this heuristic algorithm cannot guarantee that a true winning candidate is found, we show that in practice, close approximations are obtained. [ABSTRACT FROM AUTHOR]

This paper introduces a computational approach to support concept selection in multi-objective design. It is motivated by: (1) a common need to delay some decisions during conceptual design due to the presence of uncertainties; and (2) intentional delay of decisions for the purpose of maintaining several optional concepts, as suggested by the concurrent engineering procedure of Toyota. Here, for the first time, a multi-objective set-based concept (SBC) selection problem with delayed decisions is formulated and solved. SBCs are conceptual solutions, which are represented by sets of particular solutions, with each concept having a one-to-many relation with the objective space. Several novel notions, such as higher-level concepts, multi-model concepts and robust concepts to delayed decisions, are defined and used. These lead to an auxiliary multi-objective decision problem. The auxiliary objectives are concept optimality and variability, both paramount to concept selection, with concept variability strongly supporting the idea of intentionally keeping several useful alternatives as long as possible. Academic and engineering examples are provided to demonstrate the proposed approach and its applicability to real-life problems. The results demonstrate that the suggested technique may well support the process of delayed decision either when needed or when deliberately done. [ABSTRACT FROM AUTHOR]

One of the possible uses of the global positioning satellite permanent stations is to use them as a datum reference when a new base station is established in a geodetic or surveying project. However, the actual procedure is not always obvious. Combining a number of permanent stations in the process involves important decisions that the analyst must make, which can alternate the results dramatically. Important network design aspects that must be addressed are, for example, how many permanent stations should be involved in the process; how long should the session duration be; how should one constrain the permanent stations in the adjustment procedure; and so forth. This paper suggests an algorithm based on multibaseline processing, minimum constraints, and free net adjustment concepts, in order to produce a base station with reliable coordinates and realistic accuracy, while using one or more permanent stations. In order to demonstrate the algorithm and to support the conclusions, it presents numerical examples from the Permanent Stations Array in the State of Israel, processed at the Technion—Israel Institute of Technology, using GAMIT software. [ABSTRACT FROM AUTHOR]

Remote sensing of land surface temperature (LST) from the thermal band data of Landsat Thematic Mapper (TM) still remains unused in comparison with the extensive studies of its visible and near-infrared (NIR) bands for various applications. The brightness temperature can be computed from the digital number (DN) of TM6 data using the equation provided by the National Aeronautics and Space Administration (NASA). However, a proper algorithm for retrieving LST from the only one thermal band of the sensor still remains unavailable due to many difficulties in the atmospheric correction. Based on thermal radiance transfer equation, an attempt has been made in the paper to develop a mono-window algorithm for retrieving LST from Landsat TM6 data. Three parameters are required for the algorithm: emissivity, transmittance and effective mean atmospheric temperature. Method about determination of atmospheric transmittance is given in the paper through the simulation of atmospheric conditions with LOWTRAN 7 program. A practicable approach of estimating effective mean atmospheric temperature from local meteorological observation is also proposed in the paper when the in situ atmospheric profile data is unavailable at the satellite pass, which is generally the case in the real world especially for the images in the past. Sensitivity analysis of the algorithm indicates that the possible error of ground emissivity, which is difficult to estimate, has relatively insignificant impact on the probable LST estimation error δT, which is sensible to the possible error of transmittance δτ6 and mean atmospheric temperature δT[sub a]. Validation of the simulated data for various situations of seven typical atmospheres indicates that the algorithm is able to provide an accurate LST retrieval from TM6 data. The LST difference between the retrieved and the simulated ones is less than 0.4°C for most situations. Application of the algorithm to the sand dunes across the Israel-Egypt border results in a reasonable LST estimation of the region. Based on this LST estimation, spatial variation of the interesting thermal phenomenon has been analysed for comparison of LST difference across the border. The result shows that the Israeli side does have significantly higher surface temperature in spite of its denser vegetation cover than the Egyptian side where bare sand is prevalent. [ABSTRACT FROM AUTHOR]

This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006-2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year.

Introduction: Lesions of the upper digestive tract due to ingestion of caustic agents still represent a major medical and surgical emergency worldwide. The work-up of these patients is poorly defined and no clear therapeutic guidelines are available. Purpose of the study: The aim of this study was to provide an evidence-based international consensus on primary and secondary prevention, diagnosis, staging, and treatment of this life-threatening and potentially disabling condition. Methods: An extensive literature search was performed by an international panel of experts under the auspices of the World Society of Emergency Surgery (WSES). The level of evidence of the screened publications was graded using the Oxford 2011 criteria. The level of evidence of the literature and the main topics regarding foregut caustic injuries were discussed during a dedicated meeting in Milan, Italy (April 2015), and during the 3rd Annual Congress of the World Society of Emergency Surgery in Jerusalem, Israel (July 2015). Results: One-hundred-forty-seven full papers which addressed the relevant clinical questions of the research were admitted to the consensus conference. There was an unanimous consensus on the fact that the current literature on foregut caustic injuries lacks homogeneous classification systems and prospective methodology. Moreover, the non-standardized definition of technical and clinical success precludes any accurate comparison of therapeutic modalities. Key recommendations and algorithms based on expert opinions, retrospective studies and literature reviews were proposed and approved during the final consensus conference. The clinical practice guidelines resulting from the consensus conference were approved by the WSES council. Conclusions: The recommendations emerging from this consensus conference, although based on a low level of evidence, have important clinical implications. A world registry of foregut caustic injuries could be useful to collect a homogeneous data-base for prospective clinical studies that may help improving the current clinical practice guidelines. [ABSTRACT FROM AUTHOR]

This year the Israeli Ministry of Education has decided to increase its support and involvement in the IOI project. The main goals of the increased involvement were to expose the project to a wider audience, and to expand the team selection and training process. For the first time, a regional competition was conducted before the national competition. In this paper we describe the aims, scope, and contents of the regional and national competitions, and provide some statistics about the students' backgrounds and views about these competitions. [ABSTRACT FROM AUTHOR]

Realizing the importance of teaching efficiency at early stages of the program of study in computer science (CS) on one hand, and the difficulties encountered when introducing this concept on the other, we advocate a different didactic approach in the introductory CS course (CS1). This paper describes the approach as it is used at the Open University of Israel (OUI). The OUI, a distance teaching institution with no prior educational requirements, runs a full-fledged CS program. Because of its open door policy, the dropout rate, especially in introductory courses, as well as the percentage of failures, is very high. Using the new approach has raised the percentage of students who pass the course. The new approach advocates integrating three-part questions which ask not only to identify the algorithmic problem that a given algorithm solves and to analyze its complexity, but also to design a new algorithm that performs the same task, while increasing efficiency by an order of magnitude, not only by a constant factor. The research we conducted to examine the implications of using this approach is described here. [ABSTRACT FROM AUTHOR]

Religion plays a central role in clients' identities, their behaviors, and their contacts with professionals. Such influence on professionals' practice is evident in cases of clients with intellectual disability and mental health illnesses in Israel. The article examines the tendency of Muslim social worker to prefer religious recommendations (following the qadi's decision) regarding the rights of marriage/divorce and child custody for parents with Mental Illness (MI) or Intellectual Disability Disorders (IDD) in simulated vignettes court cases. The study analyzed vignettes simulating Muslim religious (Sharia) court cases. Muslim social workers (138) completed a background and religiosity questionnaires as well as their response to 25 vignettes simulated court rulings adapted for this study. The decision of the qadi was rephrased in a short statement and appended after each case of the 25, this decision was considered as a religious recommendation since it based on religious consideration. The participants were asked whether they agree or disagree with these recommendations. Muslim social workers tended to consider religious recommendation when the family of the person with MI was described as religious. The discussed issue (marriage/divorce or child custody) was found to explain their tendency to adopt religious recommendation in cases of IDD. Implications of our findings are discussed with respect to social work practice and education. [ABSTRACT FROM AUTHOR]

This article focuses on the three Israeli digital campaigns during 2019–20 elections through their most prominent negative trends, namely: fake news, accounts and identities; politicians' chat bots; influence and interruption networks, illegal information accumulation on Israeli citizens via social media and voting apps; anonymous and fake spam, and a complete lack of compliance with the statutory and regulatory framework. With technology's speedy advancement, legal tools' lagging, and political actors' exploitation of the situation to their benefit, it seems that these campaigns, setting forth a fifth phase of political communication – Algorithmic Campaigns – constitute a rather bleak and grim future, as far as elections are concerned, thereby calling for rethinking. [ABSTRACT FROM AUTHOR]

Introduction: As the Syrian civil war continues, medical care of the injured remains a priority for health facilities receiving casualties. Ziv Medical Centre, the closest hospital in Israel to the Syrian border, has received 500 casualties since February 2013. Seventeen of these patients had vascular injuries. This research reports the care of these seventeen patients and explores the challenges of treatment in patients with little antecedent clinical history and improvised initial care that may be complicated by delay to definitive care, sepsis and limb ischaemia.Method: Electronic and paper patient records were examined. Descriptive case series data are presented.Results: Fifteen of the 17 patients were male. The mean age was 20 years (range 8-30 years). Causes of injury included gunshot wounds (4 patients), shrapnel (multi-fragment) injury (12 patients), and 1 patient was run over and dragged behind a car. The time from injury to transfer to definitive care ranged from 5h to 7 days (mean 43 h). All but one patient had associated non-vascular multiple-trauma. Thirteen patients presented with limb ischaemia. Four patients had arterio-venous fistula (AVF) or pseudoaneurysm. There were 5 upper and 10 lower limb major vascular injuries. Three patients had neck vessel injuries. All patients were investigated with CT angiography and underwent surgical or endovascular intervention. In 12 patients, 4 vessels were debrided and re-anastomosed and 13 vessels bypassed. Endovascular repair was performed in 4 patients. After initial revascularisation, 4 patients went on to amputation. There were no deaths.Conclusions: The injuries treated are heterogeneous, and reflect the range of high energy vascular trauma expected in conflict. The broad range of vascular solutions required to optimise outcomes, in particular, limb salvage, in turn, reflect the challenges of dealing with such injuries, especially within the context of sepsis, ischaemia and delay. As war continues, there is a pressing need to address the needs of patients with high energy injuries in austere environments where there is a dearth of health resources and where definitive care may be days away. [ABSTRACT FROM AUTHOR]

There is an important, long-standing debate regarding the universality vs. specificity of trauma-related mental health symptoms in socio-culturally and linguistically diverse population groups, such as refugees and asylum seekers. Network theory, an emerging development in the field of psychological science, provides a novel data analytic methodology to evaluate and empirically examine long-standing questions about the structure and function of posttraumatic stress symptoms. We sought to empirically model the functional network of posttraumatic stress symptoms among East African refugees who survived multiple potentially traumatic events. A sample of 148 Sudanese and Eritrean male asylum seekers (M (SD)age = 32.60(7.13) were recruited from the community in Israel. The nature and function(s) of posttraumatic symptoms (Harvard Trauma Questionnaire) were modeled using regularized partial correlation models to derive a network of symptoms. Spinglass and exploratory graph analysis walktrap algorithms were then used to identify functional "circuits of symptoms" or clusters of nodes within the network. Analyses revealed a functional symptom circuitry that shares features with the predominant western model of posttraumatic stress disorder; as well as unique functional clusters of symptoms inconsistent with nosology and symptomatology observed in studies of Western populations. Findings may have important implications for theory, classification, assessment, candidate mechanisms that may drive and maintain posttraumatic stress, and in turn may inform prevention or treatment for socio-culturally diverse forcibly displaced population groups. [ABSTRACT FROM AUTHOR]

This paper begins with a brief review of the operational aspects of bus scheduling at Egged (The Israel National Bus Carrier), and their experience with an optimal bus scheduling algorithm. Due to the limitations of this algorithm, Egged Management has decided it is still not justified to replace the manually and currently used planning procedures (comprised of 60 schedulers using Gantt charts). Consequently, an approximate procedure incorporating a man/computer interface was requested which would allow the inclusion of practical considerations that experienced schedulers may wish to introduce in the schedule. Due to its visual nature, the deficit function was selected as a natural tool to form the basis of such a man-machine interactive scheduling procedure. A deficit function defines the net number of departures required at each terminal up to and including time t. According to the well-known fleet size formula, the minimum number of vehicles required to service a multiterminal fixed schedule of trips is equal to the sum of the maximal deficits at all terminals. As deficit function theory stops at a fixed schedule of trips, it was necessary to develop procedures to (1) primarily determine when and where to insert deadheading trips, and (2) secondarily include such considerations as garage limitations, inclusion of refueling trips, and driver limitations. The final algorithm is capable of generating schedules automatically in a purely computer mode. In an interactive mode it allows the user to select one of several computer suggested improvements or to interject his own suggestions and immediately see the effects on the final schedule through observation of the deficit functions on a CRT or computer generated output. [ABSTRACT FROM AUTHOR]

Visitors to museums and other cultural heritage sites encounter a wealth of exhibits in a variety of subject areas, but can explore only a small number of them. Moreover, there typically exists rich complementary information that can be delivered to the visitor about exhibits of interest, but only a fraction of this information can be consumed during the limited time of the visit. Recommender systems may help visitors to cope with this information overload. Ideally, the recommender system of choice should model user preferences, as well as background knowledge about the museum's environment, considering aspects of physical and thematic relevancy. We propose a personalized graph-based recommender framework, representing rating history and background multi-facet information jointly as a relational graph. A random walk measure is applied to rank available complementary multimedia presentations by their relevancy to a visitor's profile, integrating the various dimensions. We report the results of experiments conducted using authentic data collected at the Hecht museum. [ABSTRACT FROM AUTHOR]

Objective To test the feasibility of classifying emergency department patients into severity grades using data mining methods. Design Emergency department records of 402 patients were classified into five severity grades by two expert physicians. The Naïve Bayes and C4.5 algorithms were applied to produce classifiers from patient data into severity grades. The classifiers' results over several subsets of the data were compared with the physicians' assessments, with a random classifier, and with a classifier that selects the maximal-prevalence class. Measurements Positive predictive value, multiple-class extensions of sensitivity and specificity combinations, and entropy change. Results The mean accuracy of the data mining classifiers was 52.94 ± 5.89%, significantly better ( P < 0.05) than the mean accuracy of a random classifier (34.60 ± 2.40%). The entropy of the input data sets was reduced through classification by a mean of 10.1%. Allowing for classification deviations of one severity grade led to mean accuracy of 85.42 ± 1.42%. The classifiers' accuracy in that case was similar to the physicians' consensus rate. Learning from consensus records led to better performance. Reducing the number of severity grades improved results in certain cases. The performance of the Naïve Bayes and C4.5 algorithms was similar; in unbalanced data sets, Naïve Bayes performed better. Conclusions It is possible to produce a computerized classification model for the severity grade of triage patients, using data mining methods. Learning from patient records regarding which there is a consensus of several physicians is preferable to learning from each physician's patients. Either Naïve Bayes or C4.5 can be used; Naïve Bayes is preferable for unbalanced data sets. An ambiguity in the intermediate severity grades seems to hamper both the physicians' agreement and the classifiers' accuracy. [ABSTRACT FROM AUTHOR]

The study aimed to examine the factor structure of the Obsessive Beliefs Questionnaire (OBQ), the most widely used measure of dysfunctional beliefs in obsessive—compulsive disorder (OCD). Multiple exploratory methods (exploratory factor analysis, cluster analysis by variable, multidimensional scaling) were used to examine the questionnaire. Confirmatory factor analyses were also performed in two large nonclinical samples from Australia (N = 1,234) and Israel ( N = 617). Our analyses suggested a four-factor solution with 38 items, where threat and responsibility formed separate dimensions (the “OBQ-TRIP”). This version had superior fit statistics across the two divergent confirmatory samples, when compared with four alternative models suggested by previous authors. Of the OBQ dimensions, the threat scale correlated most strongly with OCD symptom measures, even when controlling for depression. A short, 20-item version of the scale is offered for further study. Implications and limitations are discussed. [ABSTRACT FROM PUBLISHER]

Background: While cough is an important defence mechanism of the respiratory system, its chronic presence is bothersome and may indicate the presence of a serious disease. We hereby describe the validation process of a novel cough detection and counting technology (PulmoTrack-CC™, KarmelSonix, Haifa, Israel). Methods: Tracheal and chest wall sounds, ambient sounds and chest motion were digitally recorded, using the PulmoTrack® hardware, from healthy volunteers coughing voluntarily while (a) laying supine, (b) sitting, (c) sitting with strong ambient noise, (d) walking, and (e) climbing stairs, a total of 25 minutes per subject. The cough monitoring algorithm was applied to the recorded data to detect and count coughs. The detection algorithm first searches for cough 'candidates' by identifying loud sounds with a cough pattern, followed by a secondary verification process based on detection of specific characteristics of cough. The recorded data were independently and blindly evaluated by trained experts who listened to the sounds and visually reviewed them on a sonogram display. The validation process was based on two methods: (i) Referring to an expert consensus as gold standard, and comparing each cough detected by the algorithm to the expert marking, we marked True and False, positive and negative detections.These values were used to evaluate the specificity and sensitivity of the cough monitoring system. (ii) Counting the number of coughs in longer segments (t = 60 sec, n = 300) and plotting the cough count vs. the corresponding experts' count whereby the linear regression equation, the regression coefficient (R2) and the jointdistribution density Bland-Altman plots could be determined. Results: Data were recorded from 12 volunteers undergoing the complete protocol. The overall Specificity for cough events was 94% and the Sensitivity was 96%, with similar values found for all conditions, except for the stair climbing stage where the Specificity was 87% with Sensitivity of 97%. The regression equation between the PulmoTrack-CC™ cough event counts and the Experts' determination was with R² of 0.94. Discussion: This validation scheme provides an objective and quantitative assessment method of a cough counting algorithm in a range of realistic situations that simulate ambulatory monitoring of cough. The ability to detect voluntary coughs under acoustically challenging ambient conditions may represent a useful step towards a clinically applicable automatic cough detector. [ABSTRACT FROM AUTHOR]