Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Adjustable Autonomy for the Real World

Adjustable autonomy refers to entities dynamically varying their own autonomy, transferring decision-making control to other entities (typically agents transferring control to human users) in key situations. Determining whether and when such transfers-of-control should occur is arguably the fundamental research problem in adjustable autonomy. Previous work has investigated various approaches to addressing this problem but has often focused on individual agent-human interactions. Unfortunately, domains requiring collaboration between teams of agents and humans reveal two key shortcomings of these previous approaches. First, these approaches use rigid one-shot transfers of control that can result in unacceptable coordination failures in multiagent settings. Second, they ignore costs (e.g., in terms of time delays or effects on actions) to an agent's team due to such transfers-of-control. To remedy these problems, this article presents a novel approach to adjustable autonomy, based on the notion of a transfer-of-control strategy. A transfer-of-control strategy consists of a conditional sequence of two types of actions: (i) actions to transfer decision-making control (e.g., from an agent to a user or vice versa) and (ii) actions to change an agent's pre-specified coordination constraints with team members, aimed at minimizing miscoordination costs. The goal is for high-quality individual decisions to be made with minimal disruption to the coordination of the team. We present a mathematical model of transfer-of-control strategies. The model guides and informs the operationalization of the strategies using Markov Decision Processes, which select an optimal strategy, given an uncertain environment and costs to the individuals and teams. The approach has been carefully evaluated, including via its use in a real-world, deployed multi-agent system that assists a research group in its daily activities.
When to Expect Negative Diffusion-Weighted Images in Stroke and Transient Ischemic Attack

Background and Purpose— The frequency of DWI negative cerebral ischemia and clinical factors associated with such a circumstance is not well understood. Methods— We performed MRI including diffusion-weighted imaging (DWI) in patients with stroke and transient ischemic attack (TIA) within 24 hours of symptom onset and again at 30 days. Results— Of 401 patients, 103 (25.6%) had an initial negative DWI study. In the DWI negative group, among the stroke patients, 6/26 (23.1%) had infarcts on follow-up MRI (4 lacunar and 2 posterior circulation syndromes) and 1 had a rMTT deficit. Among the TIA patients, 4/63 (6.3%) showed rMTT deficits and 2/63 (3.2%) had infarcts on follow-up MRI. Conclusions— Baseline perfusion weighted imaging sequences may detect ischemia in a small proportion of DWI negative cases. Only those with brain stem location or lacunar syndrome were DWI negative initially and yet had a follow-up imaging confirmation of infarct or a final clinical diagnosis of stroke.
A Method for the Monthly Electricity Demand Forecasting in Colombia based on Wavelet Analysis and a Nonlinear Autoregressive Model

This paper proposes a monthly electricity forecast method for the National Interconnected System (SIN) of Colombia. The method preprocesses the time series using a Multiresolution Analysis (MRA) with Discrete Wavelet Transform (DWT); a study for the selection of the mother wavelet and her order, as well as the level decomposition was carried out. Given that original series follows a non-linear behaviour, a neural nonlinear autoregressive (NAR) model was used. The prediction was obtained by adding the forecast trend with the estimated obtained by the residual series combined with further components extracted from preprocessing.A bibliographic review of studies conducted internationally and in Colombia is included, in addition to references to investigations made with wavelet transform applied to electric energy prediction and studies reporting the use of NAR in prediction.
Selection and placement of best management practices used to reduce water quality degradation in Lincoln Lake watershed

An increased loss of agricultural nutrients is a growing concern for water quality in Arkansas. Several studies have shown that best management practices (BMPs) are effective in controlling water pollution. However, those affected with water quality issues need water management plans that take into consideration BMPs selection, placement, and affordability. This study used a nondominated sorting genetic algorithm (NSGA‐II). This multiobjective algorithm selects and locates BMPs that minimize nutrients pollution cost‐effectively by providing trade‐off curves (optimal fronts) between pollutant reduction and total net cost increase. The usefulness of this optimization framework was evaluated in the Lincoln Lake watershed. The final NSGA‐II optimization model generated a number of near‐optimal solutions by selecting from 35 BMPs (combinations of pasture management, buffer zones, and poultry litter application practices). Selection and placement of BMPs were analyzed under various cost solutions. The NSGA‐II provides multiple solutions that could fit the water management plan for the watershed. For instance, by implementing all the BMP combinations recommended in the lowest‐cost solution, total phosphorous (TP) could be reduced by at least 76% while increasing cost by less than 2% in the entire watershed. This value represents an increase in cost of $5.49 ha−1 when compared to the baseline. Implementing all the BMP combinations proposed with the medium‐ and the highest‐cost solutions could decrease TP drastically but will increase cost by $24,282 (7%) and $82,306 (25%), respectively.
A New Approach to Emotion Assessment Based on Biometric Data

Several knowledge areas such as psychology, medicine and computer science have been devoting serious efforts regarding emotional state definition, identification and assessment. This project consists in an automatic emotion assessment tool based on biometric data acquisition supported by low-budget biometric devices as a electroencephalograph and a galvanic skin response. The classification is grounded on data analysis and processing of standard emotional induction methods. The numerous conducted experimental sessions,alongside with the developed support tools, allowed the extraction of conclusions such as the capability of effectively performing automatic classification of the subjectpsilas predominant emotional state. The developed tool's success rate, validated against self assessment interviews, was approximately 75%. It was also experimentally concluded that female subjects are emotionally more active and easily induced than males.
The broad-band X-ray spectrum of the blazar PKS B1830-211 by Chandra and INTEGRAL

In this paper we present a broad-band study of the X-ray emission of the blazar PKS 1830−211 based on Chandra and INTEGRAL observations. Notwithstanding the high redshift (z = 2.507), it is a bright X-ray source (F(2-10 keV) � 10 −11 erg cm −2 s −1 ), due to gravitational lensing by an intervening galaxy at z = 0.89. Previous X-ray ob- servations attribute the observed absorption at E < 2 keV to the lensing galaxy. Our analysis, although not in contrast with this hypothesis, suggests also the possibility of an intrinsic (ionized) absorption, taking place at the front side of the jet. This scenario is also supported by some evidence, in the same data, of a feature observed at 2.15 keV which can be interpreted as a blueshifted iron line (v/c � 0.18). The SED of PKS 1830−211 can be well modelled by combining a Synchrotron Self-Compton component and an external source of photons to be scattered up to γ-ray energies by relativistic electrons moving outward in the jet. The main source of low energy photons is a dust torus at the temperature of 10 3 K as expected in MeV blazars.
Sampled-data containment control in second-order multi-agent systems with event-triggered transmission

The paper is concerned with event-triggered sampled-data containment control in second-order multi-agent systems with directed topology. Under the transmission scheme, the event-trigged condition can be only intermittently detected at sampling constants. With the proposed protocol, the containment control of the multi-agent systems can be transformed into the stability of a time-delay system. By constructing a Lyapunov-Krasovskii functional, a stability criterion is derived. Finally, a numerical simulation is provided to illustrate the effectiveness of the obtained method.
Survey and comparison of the project management softwares used by engineering , procurement and construction companies

This paper presents a survey and comparison of a series of project management softwares used by engineering, procurement and construction companies in order to evaluate the best software tools based on chosen features. The evaluation was carried out through the well known Analytic Hierarchy Process (AHP) method. After a brief description of the features required by a project management tool and after a brief description of the software tools in exam, the authors applied the AHP method to the softwares cross-evaluating each of their features. Key-Words: -EPC, Plant Construction .
Correlation of CD2 binding and functional properties of multimeric and monomeric lymphocyte function-associated antigen 3

LFA-3 was purified with an intact (mLFA-3) or an enzymatically removed membrane-anchoring domain (sLFA-3). Gel filtration and sucrose gradient sedimentation showed sLFA-3 to be a single highly glycosylated polypeptide chain in solution, while mLFA-3 formed micelles of 8 LFA-3 monomers. 125I-mLFA-3 bound to Jurkat T leukemic cell surface CD2 with much higher avidity than sLFA-3. mLFA-3 binding had characteristics of a multivalent interaction with cell surface CD2 and had an avidity of 1.5 nM for Jurkat cells and 12 nM for resting T cells. Two CD2 mAbs tested did not block mLFA-3 binding: 9-1 and CD2.1. These mAbs were tested in combination with LFA-3 for their ability to activate T cells. The combination of mLFA-3 and CD2.1 mAbs induced a rapid increase in cytosolic free Ca2+ in Jurkat cells which was proportional to mLFA-3 occupation of CD2 sites. sLFA-3 showed no activity in the Ca2+ flux assay. The combination of mLFA-3 and the CD2.1 mAbs significantly stimulated proliferation of PBMC. The combination of mLFA-3 and 9-1 mAbs was weakly or not mitogenic for the same cells. The combination of CD2.1 and sLFA-3 at concentrations up to 480 nM was not consistently mitogenic. Therefore, monomeric LFA-3/CD2 interaction appears to have a relatively low affinity, while multimeric LFA-3 binds with high avidity. T cell activation by binding of LFA-3 to CD2 appears to require occupation of 10(4) to 10(5) CD2 sites, which is likely to occur during adhesion, but is rare in receptor systems with soluble ligands.
Compressed learning of high-dimensional sparse functions

This paper presents a simple randomised algorithm for recovering high-dimensional sparse functions, i.e. functions ƒ : [0, 1]<sup>d</sup> → ℝ which depend effectively only on k out of d variables, meaning ƒ(x<inf>1</inf>, …, x<inf>d</inf>) = g(x<inf>i1</inf>, …, x<inf>ik</inf> ), where the indices 1 ≤ i<inf>1</inf> &#60; i<inf>2</inf> &#60; … &#60; i<inf>k</inf> ≤ d are unknown. It is shown that (under certain conditions on g) this algorithm recovers the k unknown coordinates with probability at least 1–6 exp(−L) using only O(k(L+log k)(L+log d)) samples of ƒ.
The Impact of Oxide Traps Induced by SOI Thickness on Reliability of Fully Silicide Metal-Gate Strained SOI MOSFET

In this letter, we investigate the effects of oxide traps induced by various silicon-on-insulator (SOI) thicknesses (<i>T</i> <sub>SOI</sub>) on the performance and reliability of a strained SOI MOSFET with SiN-capped contact etch stop layer (CESL). Compared to the thicker <i>T</i> <sub>SOI</sub> device, the thinner <i>T</i> <sub>SOI</sub> device with high-strain CESL possesses a higher interface trap (<i>N</i> <sub>it</sub>) density, leading to degradation in the device performance. On the other hand, however, the thicker <i>T</i> <sub>SOI</sub> device reveals inferior gate oxide reliability. From low-frequency noise analysis, we found that thicker <i>T</i> <sub>SOI</sub> has a higher bulk oxide trap (<i>N</i> <sub>BOT</sub>) density, which is induced by larger strain in the gate oxide film and is mainly responsible for the inferior TDDB reliability. Presumably, the gate oxide film is bended up and down for the p- and nMOSFETs, respectively, by the net stress in thicker <i>T</i> <sub>SOI</sub> devices in this strain technology.
Linguistics tools to develop an Arabic syntax analyzer

This study presents a formal description of a linguistic system for developing an Arabic syntax analyzer based combinatorial grammar. In this context we will present several formal concepts to redefine the structure of the Arabic language in order to adapt it to the automatic processing of at syntactic level, such as support verb, nominalization, and other operators. These concepts provide an effective framework for the implementation of language engineering techniques aimed at integrating the Arabic language within the NLP community.
Absorption, Distribution, Metabolism, and Excretion Considerations for the Development of Antibody-Drug Conjugates

Antibody-drug conjugates (ADCs) are a class of therapeutics that are designed to deliver potent small-molecule drugs selectively to cells that express a specific target antigen while limiting systemic exposure to the drug. This is accomplished by conjugating a potent drug onto an antibody-based therapeutic with a linker that is exquisitely stable in plasma. The development of an effective ADC requires optimizing a number of design elements and an extensive understanding of absorption, distribution, metabolism/catabolism, and elimination (ADME) processes for the ADC construct. Furthermore, as ADCs are a combination of an antibody and small-molecule drug, understanding key aspects of the ADME of each individual component is needed. This review aims to provide considerations for the development of ADCs from an ADME point of view.
Face expression recognition based on equable principal component analysis and linear regression classification

In this paper, we present a novel expression recognition method. Equable Principal Component Analysis (EPCA) is used as expression features representation and Linear Regression Classification (LRC) is employed as expression classifiers. EPCA maintains the useful information of the original image while reducing the dimension of feature vector data. LRC deals with the problem of face recognition as a linear regression problem. Experiments of human images are performed on the Yale and JAFFE database. Compared to the state-of-art approaches, the recognition rate of the proposed method is higher. Therefore, the combination of LRC and EPCA for facial expression recognition is feasible.
The study of multi-dimensional reverse channels for construction machinery remanufacturing

For the need of sustainable development, the importance of the reverse collection and remanufacturing has been widely recognized in the literature and in practice. In this paper, we analyzed three reverse channels extensively used in the remanufacturing practice, i.e. retailer collection, manufacturer collection and third party collection. The results address that the choice of single one reverse channel can hardly satisfy the demand of the construction machinery remanufacturing companies with complex market demand and the necessity of establishing multi-dimensional reverse channels which combine the application of multiple reverse channels. Specifically, considering that one remanufacturer already has an excellent forward supply chain network and suitable reverse channels to choose, we proposed a special reverse model and applied it to an actual case. According to the analysis, the conclusions can be summarized as: (1) for the remanufacturer, the third party collection is extensively necessary to him for the reduction of the expenses on establishing unnecessary reverse network, (2) the remanufacturer should make a balance between the retailer collection and third party collection to maximize the profit, while the fee paid to the third party is relatively low and the collection cost he made to the retailer collection is relatively high, the rate of the investment in third party collection could be increased in corresponding, and vice versa.
Optimizing age-of-information in a multi-class queueing system

We consider the age-of-information in a multi-class M/G/1 queueing system, where each class generates packets containing status information. Age of information is a relatively new metric that measures the amount of time that elapsed between status updates, thus accounting for both the queueing delay and the delay between packet generation. This gives rise to a tradeoff between frequency of status updates, and queueing delay. In this paper, we study this tradeoff in a system with heterogenous users modeled as a multi-class M/G/1 queue. To this end, we derive the exact peak age-of-Information (PAoI) profile of the system, which measures the “freshness” of the status information. We then seek to optimize the age of information, by formulating the problem using quasiconvex optimization, and obtain structural properties of the optimal solution.
Secondary Hyperparathyroidism Is Associated with Higher Cost of Care among Chronic Kidney Disease Patients with Cardiovascular Comorbidities

Background: Chronic kidney disease (CKD) is associated with high morbidity and mortality, and incurs a substantial cost. Secondary hyperparathyroidism (SHPT) is a major complication associated with CKD and has been linked with cardiovascular disease, leading to poor outcomes. Methods: We analyzed retrospective studies for the prevalence of congestive heart failure (CHF) and acute myocardial infarction/ischemic heart disease (AMI/IHD) in pre-dialysis CKD patients to estimate the additional hospitalization cost incurred secondary to high parathyroid hormone (PTH) levels. Two models were developed to estimate the contribution of elevated PTH levels towards hospitalization costs in CKD patients with CHF and AMI/IHD. Results: Cost contributions were estimated for the time intervals relative to initiation of dialysis, with the largest contributions estimated for the 3- to 1-month period prior to initiation of dialysis, USD 205.24 per patient-month at risk for CHF and USD 69.44–111.75 per patient-month at risk for AMI/IHD, without and with major complications, respectively. Conclusion: Higher PTH levels are associated with a high prevalence of CHF and AMI/IHD. Our cost analyses show that elevated PTH levels contribute significantly toward the overall cost of care among CKD patients with CHF and AMI/IHD. The contribution of elevated PTH levels toward hospitalization cost is highest during the months directly leading up to initiation of dialysis. Further studies are required to evaluate the relationship between hyperparathyroidism and cardiovascular disease, and its impact on economic outcomes.
A Formal Approach to Ontology-Based Semantic Match of Skills Descriptions

Skills management has been recently acknowledged as one of the key fac- tors to adequately face the increasing competitiveness between knowledge intensive companies. In this paper we present a formal approach to Ontology-Based Semantic Matchmaking between Skills demand and supply, devised as a virtual marketplace of knowledge. In such a knowledge market metaphor, skills are a peculiar kind of good that has distinguishing characteristics with respect to traditional assets. Buyers are entities that need the skills of people, such as projects, departments and organizations; sellers are workers that offer their own skills. The formal framework supports the semantic match of descriptions provided by de- manders and sellers of skills. In particular our approach, based on Description Log- ics formalization and reasoning, overcomes simple subsumption matching and allows match ranking and categorization. The implementation of the approach in a prototype system, which embeds a NeoClassic reasoner, is also described.
3D ultrasound imaging of tissue anisotropy using spatial coherence: Comparison between plane waves and diverging waves

After a myocardium infarction, cell loss is irremediable leading to a progressive local disorganization and change in the tissue structure altering heart function. An imaging method able to render the local tissue directivity would be a powerful tool to characterize the extent of the lesion. In this field, diffusion MRI is the reference. Because of its long acquisition time and the difficulty to tackle organ motion, faster imaging strategies such as ultrasound, are mandatory for such clinical applications. One of them is the spatial coherence of US waves, already developed in focused and plane waves (2D and 3D) but never in diverging waves [Papadacci, UFFC 2014]. The advantage of diverging waves is to create an image with a higher field of view, which is more appropriate to in vivo cardiac applications. The purpose of this work is to use 2D spatial coherence to determine the fibers orientation and to compare results in 3D steered plane and diverging waves.
UKKO: Enriching Persuasive Location based Games with Environmental Sensor Data

The number of children walking to school is at an all-time low and car use on the rise. The walk to school is seen as an opportunity to promote exercise and tackle the effects of an increasingly sedentary lifestyle amongst young people. At the same time we have a growing understanding of the harmful effects of air pollution on our health. Walking to school would not only make for healthier kids, it would reduce traffic and create a healthier, safer environment but we still drive our kids to school. This paper describes the initial design and development of UKKO, a novel persuasive game to encourage walking to school and engagement with local data. UKKO uses real time environmental data captured by the player to create a virtual environment for a digital pet. The more the student walks and avoids areas of high pollution the more healthy their pet.
Surface Mesh Evaluation

Geometric criteria, based on geometric feature analysis, are presented in this paper to deal with the evaluation of nite element surface meshes. Theoretical aspects as well as numerical examples are provided in the context of nite element methods. The proposed measures can be used to govern surface mesh modiication algorithms and are useful to validate the surface meshes within a general mesh adaption scheme for which the size map is provided via an a posteriori error estimate.
Effect of posaconazole on the pharmacokinetics of fosamprenavir and vice versa in healthy volunteers.

OBJECTIVES To manage the interaction between fosamprenavir/ritonavir and posaconazole, we hypothesized that ritonavir can be replaced by posaconazole as an alternative booster of fosamprenavir with no significant influence on posaconazole pharmacokinetics. METHODS This was an open-label, randomized, three period, cross-over, single-centre trial in 24 healthy volunteers. All subjects received the following three treatments for 10 days, separated by washout periods of 17 days: posaconazole 400 mg twice daily; fosamprenavir/ritonavir 700/100 mg twice daily; posaconazole 400 mg twice daily with fosamprenavir 700 mg twice daily. RESULTS Twenty subjects completed the trial. Geometric mean ratios (GMR; +90% confidence interval) of posaconazole AUC and C(max) when taken with fosamprenavir versus posaconazole alone were 0.77 (0.68-0.87) and 0.79 (0.71-0.89), respectively. The GMRs of amprenavir AUC and C(max) when taken as fosamprenavir and posaconazole versus fosamprenavir/ritonavir were 0.35 (0.32-0.39) and 0.64 (0.55-0.76), respectively. No serious adverse events were reported during the trial. CONCLUSION Unboosted fosamprenavir should not be used concomitantly with posaconazole.