Miracle-dz/UniFAR-FTUs huggingface dataset:
Model of the glucose-insulin system of type-1 diabetics and optimization-based bolus calculation

In this contribution, a mathematical model of the glucose-insulin system in the case of type-1 diabetes is presented. This model and is subsequently used to determine an optimal so-called bolus dosage adapted to the diabetic patient's future behaviour. This model on the one hand is chosen with a level of detail comprising the major part of daily situations. On the other hand, it is still relatively easy to parametrize in order to be usable within a so-called bolus calculator. The validity of the model is shown using real patient measurement data and the bolus optimization is carried out in a simulation environment.
Extending query translation to cross-language query expansion with markov chain models

Dictionary-based approaches to query translation have been widely used in Cross-Language Information Retrieval (CLIR) experiments. However, translation has been not only limited by the coverage of the dictionary, but also affected by translation ambiguities. In this paper we propose a novel method of query translation that combines other types of term relation to complement the dictionary-based translation. This allows extending the literal query translation to related words, which produce a beneficial effect of query expansion in CLIR. In this paper, we model query translation by Markov Chains (MC), where query translation is viewed as a process of expanding query terms to their semantically similar terms in a different language. In MC, terms and their relationships are modeled as a directed graph, and query translation is performed as a random walk in the graph, which propagates probabilities to related terms. This framework allows us to incorporating different types of term relation, either between two languages or within the source or target languages. In addition, the iterative training process of MC allows us to attribute higher probabilities to the target terms more related to the original query, thus offers a solution to the translation ambiguity problem. We evaluated our method on three CLIR benchmark collections, and obtained significant improvements over traditional dictionary-based approaches.
Ionic Liquids as Unforeseen Assets to Fight Life-Threatening Mycotic Diseases

Ionic liquids discovery has celebrated 100 years. They consist solely of ions, one of which is typically organic and asymmetrical. Remarkable physical and chemical properties stirred their use as alternative solvents in many chemical processes. The recent demonstration of their occurrence in nature might boost their interest in biological sciences. In the search of mechanistic understandings of ionic liquids’ ecotoxicological impacts in fungi, we have analyzed the proteome, transcriptome, and metabolome responses to this chemical stress. Data illuminated new hypotheses that altered our research path – exploit ionic liquids as tools for the discovery of pathways and metabolites that may impact fungal development and pathogenicity. As we get closer to solve the primary effects of each ionic liquid family and their specific gene targets, the vision of developing antifungal ionic liquids and/or materials, by taking advantage of elegant progresses in this field, might become a reality. Task-designed formulations may improve the performance of conventional antifungal drugs, build functional coatings for reducing allergens production, or aid in the recovery of antifungal plant polymers. The frontier research in this cross-disciplinary field may provide us unforeseen means to address the global concern of mycotic diseases. Pathogenic and opportunistic fungi are responsible for numerous infections, killing annually nearly 1.5 million immunocompromised individuals worldwide, a similar rate to malaria or tuberculosis. This perspective will review our major findings and current hypotheses, contextualizing how they might bring us closer to efficient strategies to prevent and fight mycotic diseases.
Tracking the Feeding Patterns of Tsetse Flies (Glossina Genus) by Analysis of Bloodmeals Using Mitochondrial Cytochromes Genes

Tsetse flies are notoriously difficult to observe in nature, particularly when populations densities are low. It is therefore difficult to observe them on their hosts in nature; hence their vertebrate species can very often only be determined indirectly by analysis of their gut contents. This knowledge is a critical component of the information on which control tactics can be developed. The objective of this study was to determine the sources of tsetse bloodmeals, hence investigate their feeding preferences. We used mitochondrial cytochrome c oxidase 1 (COI) and cytochrome b (cytb) gene sequences for identification of tsetse fly blood meals, in order to provide a foundation for rational decisions to guide control of trypanosomiasis, and their vectors. Glossina swynnertoni were sampled from Serengeti (Tanzania) and G. pallidipes from Kenya (Nguruman and Busia), and Uganda. Sequences were used to query public databases, and the percentage identities obtained used to identify hosts. An initial assay showed that the feeds were from single sources. Hosts identified from blood fed flies collected in Serengeti ecosystem, included buffaloes (25/40), giraffes (8/40), warthogs (3/40), elephants (3/40) and one spotted hyena. In Nguruman, where G. pallidipes flies were analyzed, the feeds were from elephants (6/13) and warthogs (5/13), while buffaloes and baboons accounted for one bloodmeal each. Only cattle blood was detected in flies caught in Busia and Uganda. Out of four flies tested in Mbita Point, Suba District in western Kenya, one had fed on cattle, the other three on the Nile monitor lizard. These results demonstrate that cattle will form an integral part of a control strategy for trypanosomiasis in Busia and Uganda, while different approaches are required for Serengeti and Nguruman ecosystems, where wildlife abound and are the major component of the tsetse fly food source.
Discriminative classifiers for phonotactic language recognition with iVectors

Phonotactic models based on bags of n-grams representations and discriminative classifiers are a popular approach to the language recognition problem. However, the large size of n-gram count vectors brings about some difficulties in discriminative classifiers. The subspace Multinomial model was recently proposed to effectively represent information contained in the n-grams using low-dimensional iVectors. The availability of a low-dimensional feature vector allows investigating different post-processing techniques and different classifiers to improve recognition performance. In this work, we analyze a set of discriminative classifiers based on Support Vector Machines and Logistic Regression and we propose an iVector post-processing technique which allows to improve recognition performance. The proposed systems are evaluated on the NIST LRE 2009 task.
Optimal Locality Preserving Projection

In the past few years, the computer vision and pattern recognition community has witnessed a rapid growth of a new kind of feature extraction method, the manifold learning methods, which attempt to project the original data into a lower dimensional feature space by preserving the local neighborhood structure. Among these methods, locality preserving projection (LPP) is one of the most promising feature extraction techniques. Based on LPP, this paper proposes a novel feature extraction algorithm, Optimal Locality Preserving Projection (Optimal LPP). Optimal here means that the extracted features are statistically uncorrelated and orthogonal, which are desirable for pattern analysis applications. We compare the proposed Optimal LPP with LPP, Orthogonal Locality Preserving Projection (OLPP) and Uncorrelated Locality Preserving Projection (ULPP) on the public available data sets, FERET and CMU PIE data sets. Experimental results show that the proposed Optimal LPP achieves much higher recognition accuracies.
Thermodynamics of Lectin-Carbohydrate Interactions

The trisaccharide 3,6-di-O-(α-D-mannopyranosyl)-D-mannose, which is present in all asparagine-linked carbohydrates, was previously shown by titration microcalorimetry to bind to the lectin concanavalin A (ConA) with nearly −6 kcal mol−1 greater enthalpy change and 60-fold higher affinity than methyl-α-D-mannopyranoside (Mandal, D. K., Kishore, N., and Brewer, C. F. (1994) Biochemistry 33, 1149-1156). Similar studies of the binding of a series of monodeoxy derivatives of the α(1-3) residue of the trimannoside showed that this arm was required for high affinity binding (Mandal, D. K., Bhattacharyya, L., Koenig, S. H., Brown, R. D., III, Oscarson, S., and Brewer, C. F. (1994) Biochemistry 33, 1157-1162). In the present paper, a series of monodeoxy derivatives of the α(1-6) arm and “core” Man residue of the trimannoside as well as dideoxy and trideoxy analogs were synthesized. Isothermal titration microcalorimetry experiments establish that the 3-, 4-, and 6-hydroxyl groups of the α(1-6)Man residue of the trimannoside binds to the lectin, along with the 2- and 4-hydroxyl groups of the core Man residue and the 3- and 4-hydroxyl groups of the α(1-3)Man residue. Dideoxy analogs and trideoxy analogs showed losses of affinities and enthalpy values consistent with losses in binding of specific hydroxyl groups of the trimannoside. The free energy and enthalpy contributions to binding of individual hydroxyl groups of the trimannoside determined from the corresponding monodeoxy analogs are observed to be nonlinear, indicating differential contributions of the solvent and protein to the thermodynamics of binding of the analogs. The thermodynamic solution data agree well with the recent x-ray crystal structure of ConA complexed with the trimannoside (Naismith, J. H., and Field, R. A. (1996) J. Biol. Chem. 271, 972-976).
Molecular Dynamics Deformation Simulation of Carbon Nanotube Probes

Understanding of the prosperities of the carbon nanotubes (CNTs) probes is crucial when measuring surface using atomic force microscopy (AFM). In this paper, we investigate the deformation of CNTs by adding lateral forces based on molecular dynamics (MD) simulation. In the simulation, Tersoff many-body potential function is used to describe the interaction between atoms. The movement of CNTs is periodic vibration, which is different from traditional material. We analyzed the vibration of different CNTs including single-walled carbon nanotubes (SWCNTs) and sharpened CNTs. Similarities and differences between different CNTs during the deformation are illustrated. It is shown that sharpened CNTs have better stiffness without declining the resolution of AFM. By analyzing the results obtained from the MD simulation, it is found that the sharpened CNTs may be more suitable as AFM probes.
Radiological sinus lift: a new minimally invasive CT-guided procedure for maxillary sinus floor elevation in implant dentistry.

PURPOSE Implant therapy has become an excellent treatment modality as its inception into the modern era of dentistry. However, when patients present with advanced atrophy of the maxillary alveolar ridge, the procedure of choice to restore the anatomic bone deficiency is surgical maxillary sinus floor elevation or sinus lift. The purpose of this study was to describe the CT guided sinus lift technique and to illustrate the minimally invasive aspect of this new radiological procedure called radiological sinus lift. MATERIAL AND METHODS For this prospective study, 17 cadaver heads which met our inclusion criteria (edentulous posterior maxillary sector and bone height less than 5 mm) were analyzed using cone beam computed tomography (CBCT) and orthopantomography (OPT). CT and sinus endoscopy was used to guide each step in the procedure. The radiological sinus lift technique consists of the following four stages: Approach. A 14.5 G OstyCut needle was inserted mesial to the canine eminence, and manual drilling was performed parallel to the sinus floor. Osteotomy. An inner obturator with a blunt tip was introduced to compress bone, to push it in close proximity to the sinus membrane and finally to create an osseous window opening into the submucosal space. Lifting. The sinus lift was performed using hydrodissection with dilute iodinated contrast medium. Filling. The submucosal space was then filled with an injection of dilute collagen. Success of the radiological sinus lift procedure was defined by the presence of a dome shape visible within the maxillary alveolar recess. All cases were imaged postoperatively using OPT and maxillary CBCT. RESULTS Twelve maxillary sinuses underwent the radiological sinus floor elevation procedure. A dome shape of the Schneiderian membrane was achieved in eight maxillary sinuses (66.7%). All failures (n = 4) were caused by mucosal perforation at the time of maxillary sinus osteotomy. Mean height of membrane elevation was 12.0 mm, with a mean intervention time of 45 min. CONCLUSION This experimental study evaluates a new minimally radiological procedure for maxillary sinus floor elevation, which provides an interventional radiological alternative to the classical surgical lateral approach and achieves an equivalent success rate to that cited in the literature for the surgical approach, a low morbidity and a shorter operating time.
Systems dynamics model for decision support in risk assessment in software projects

Project management is widely studied and has several tools that aid in the efficiency and effectiveness of software production. However, in project management, numerous risk factors are involved in the development of software. These risk factors interact in a dynamic and non‐linear way, hindering decision‐making. The objective of this paper is to present a model of systems dynamics, which is a descriptive technique used for modeling and simulating systems, involving risk factors that strongly influence the development of software. The model generated is a tool that aims to assist project managers in their decision‐making. The relationships between variables were extracted from actual or empirical experiments available in the literature, thus bringing the model results closer to the real world. The model enables reproducing scenarios in which real‐world tests would be costly or dangerous to be carried out, allowing the impacts of risks in software development process to be analyzed. Copyright © 2015 John Wiley & Sons, Ltd.
Incidence and prognosis of intraabdominal hypertension in a mixed population of critically ill patients: A multiple-center epidemiological study*

Objective:Intraabdominal hypertension is associated with significant morbidity and mortality in surgical and trauma patients. The aim of this study was to assess, in a mixed population of critically ill patients, whether intraabdominal pressure at admission was an independent predictor for mortality and to evaluate the effects of intraabdominal hypertension on organ functions. Design:Multiple-center, prospective epidemiologic study. Setting:Fourteen intensive care units in six countries. Patients:A total of 265 consecutive patients admitted for >24 hrs during the 4-wk study period. Interventions:None. Measurements and Main Results:Intraabdominal pressure was measured twice daily via the bladder. Data recorded on admission were the patient demographics with Simplified Acute Physiology Score II, Acute Physiology and Chronic Health Evaluation II score, and type of admission; during intensive care stay, Sepsis-Related Organ Failure Assessment score and intraabdominal pressure were measured daily together with fluid balance. Nonsurvivors had a significantly higher mean intraabdominal pressure on admission than survivors: 11.4 ± 4.8 vs. 9.5 ± 4.8 mm Hg. Independent predictors for mortality were age (odds ratio, 1.04; 95% confidence interval, 1.01–1.06; p = .003), Acute Physiology and Chronic Health Evaluation II score (odds ratio, 1.1; 95% confidence interval, 1.05–1.15; p < .0001), type of intensive care unit admission (odds ratio, 2.5 medical vs. surgical; 95% confidence interval, 1.24–5.16; p = .01), and the presence of liver dysfunction (odds ratio, 2.5; 95% confidence interval, 1.06–5.8; p = .04). The occurrence of intraabdominal hypertension during the intensive care unit stay was also an independent predictor of mortality (relative risk, 1.85; 95% confidence interval, 1.12–3.06; p = .01). Patients with intraabdominal hypertension at admission had significantly higher Sepsis-Related Organ Failure Assessment scores during the intensive care unit stay than patients without intraabdominal hypertension. Conclusions:Intraabdominal hypertension on admission was associated with severe organ dysfunction during the intensive care unit stay. The mean intraabdominal pressure on admission was not an independent risk factor for mortality; however, the occurrence of intraabdominal hypertension during the intensive care unit stay was an independent outcome predictor.
Bandwidth-constrained distributed skyline computation

Skyline queries have been studied in centralized systems, but also in distributed environments, such as web information systems and peer-to-peer networks. Most of the existing work focuses on efficient processing of skyline queries that return the exact and complete result set. In this paper, we study skyline computation in a distributed environment under the assumption of a given upper bound on the bandwidth consumption. Supporting such a constraint is very important in a mobile environment, where data transmissions may lead to deterioration of query processing performance, while imposing high cost for the mobile device in terms of energy consumption. Therefore, the cost of transferring all data points that may contribute to the skyline result set to the querying server is often prohibitive. Our target is, given an upper bound of bandwidth consumption, to maximize the quality of the retrieved skyline approximation. For this purpose, we propose a framework for bandwidth-constrained skyline query processing, based on the intentional selection of a limited amount of data points from each participating mobile device. We propose a novel method to carefully select the most promising data points based on subspace dominations and analyze its properties. In our extensive experimental evaluation, we demonstrate that result sets of high quality are achieved, while reducing the communication cost considerably.
Will my patch make it? And how fast? Case study on the Linux kernel

The Linux kernel follows an extremely distributed reviewing and integration process supported by 130 developer mailing lists and a hierarchy of dozens of Git repositories for version control. Since not every patch can make it and of those that do, some patches require a lot more reviewing and integration effort than others, developers, reviewers and integrators need support for estimating which patches are worthwhile to spend effort on and which ones do not stand a chance. This paper crosslinks and analyzes eight years of patch reviews from the kernel mailing lists and committed patches from the Git repository to understand which patches are accepted and how long it takes those patches to get to the end user. We found that 33% of the patches makes it into a Linux release, and that most of them need 3 to 6 months for this. Furthermore, that patches developed by more experienced developers are more easily accepted and faster reviewed and integrated. Additionally, reviewing time is impacted by submission time, the number of affected subsystems by the patch and the number of requested reviewers.
On probabilistic fixpoint and Markov chain query languages

We study highly expressive query languages such as datalog, fixpoint, and while-languages on probabilistic databases. We generalize these languages such that computation steps (e.g. datalog rules) can fire probabilistically. We define two possible semantics for such query languages, namely inflationary semantics where the results of each computation step are added to the current database and noninflationary queries that induce a random walk in-between database instances. We then study the complexity of exact and approximate query evaluation under these semantics.
Probabilistic Surfel Fusion for Dense LiDAR Mapping

With the recent development of high-end LiDARs, more and more systems are able to continuously map the environment while moving and producing spatially redundant information. However, none of the previous approaches were able to effectively exploit this redundancy in a dense LiDAR mapping problem. In this paper, we present a new approach for dense LiDAR mapping using probabilistic surfel fusion. The proposed system is capable of reconstructing a high-quality dense surface element (surfel) map from spatially redundant multiple views. This is achieved by a proposed probabilistic surfel fusion along with a geometry considered data association. The proposed surfel data association method considers surface resolution as well as high measurement uncertainty along its beam direction which enables the mapping system to be able to control surface resolution without introducing spatial digitization. The proposed fusion method successfully suppresses the map noise level by considering measurement noise caused by laser beam incident angle and depth distance in a Bayesian filtering framework. Experimental results with simulated and real data for the dense surfel mapping prove the ability of the proposed method to accurately find the canonical form of the environment without further post-processing.
Personal exposure to benzene and the influence of attached and integral garages

Benzene is an air pollutant that is a recognised human carcinogen. An air quality standard has been established for ambient air in the UK to reduce the popula tion's exposure. It has been estimated that about 70% of benzene emissions to air in the UK come from petrol vehicles. A number of studies, including the Avon Longitudinal Study of Pregnancy and Childhood in the UK, have found that benzene concentrations in homes with attached or integral garages tend to be higher than in those without such garages. The present paper reviews these studies and reports a detailed investigation of five homes with either an attached or an integral garage. Indoor and outdoor locations were monitored using diffusive sampling to determine the average benzene concentration over approximately 28 days each month for 18 consecutive months (June 1998-November 1999). For one of these homes, ten years of data had shown the indoor benzene concentration to be con sistently higher than outdoors. Personal exposure monitoring of one adult in this home showed that the benzene concentration in the main bedroom was a better predictor of personal exposure than the concentration outdoors. In the homes where a car was regularly parked in the garage, 18-month aver age benzene concentrations of up to 101.3 μgm 3 were measured in the garage, which is more than six times the ambient air quality standard for benzene (16.25 μgm3 running annual average). Mean benzene values in all cars and most of the garages studied exceeded the benzene standard. Mean benzene concentrations in the room above the garage ranged from 3.7 μgm3 in one home, where the car was rarely parked in the garage, to 39.9 μgm3 in another home where a car with high benzene emissions was parked in the garage for six of the 18 months monitored. The mean benzene concentration in the room above the garage in this latter home was nearly 2.5 times the ambient air standard. The study demonstrates that there is a potential for people to have a higher exposure to benzene as a result of living in a home with an attached or integral garage. An understanding of routes of personal exposure is important to devel op effective policies to reduce risks to health.