Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy portfolio selection problem

Considers an application of a fuzzy random variable to a single index model of a portfolio selection problem. A single index model decomposes the risk on investment into the risk common to all investments caused by a market and the risk individual to each investment caused by other factors. The paper investigates the case where the rate of return on each investment can be represented with a fuzzy random variable. We propose a decision making method based both on possibility theory and on a chance constrained program in stochastic programming, and show that this problem is transformed into a deterministic equivalent problem, which is a nonlinear non-convex programming problem. Further we introduce a subsidiary problem the optimal solution of which has a close relation to that of the original problem and construct an efficient algorithm.
Robotic Ankle Training Improves Sensorimotor Functions in Children with Cerebral Palsy—A Pilot Study

Children with cerebral palsy (CP) have sensorimotor impairments including weakness, spasticity, reduced motor control and sensory deficits. Proprioceptive dysfunction compounds the decreased motor control and mobility. The aims of this paper were to (1) examine proprioceptive deficit of lower extremities of children with CP; (2) study improvement in proprioception and clinical impairments through robotic ankle training (RAT). Eight children with CP participated in a 6-week RAT with pre and post ankle proprioception, clinical, biomechanical assessment compared to the assessment of eight typically developing children (TDC). The children with CP participated in passive stretching (20 min/session) and active movement training (20 to 30 min/session) using an ankle rehabilitation robot (3 sessions/week over 6 weeks, total of 18 sessions). Proprioceptive acuity measured as the plantar and dorsi-flexion motion at which the children recognized the movement was 3.60 ± 2.28° in dorsiflexion and −3.72 ± 2.38° in plantar flexion for the CP group, inferior to that of the TDC group’s 0.94 ± 0.43° in dorsiflexion (p = 0.027) and −0.86 ± 0.48° in plantar flexion (p = 0.012). After training, ankle motor and sensory functions were improved in children with CP, with the dorsiflexion strength increased from 3.61 ± 3.75 Nm to 7.48 ± 2.75 Nm (p = 0.018) and plantar flexion strength increased from −11.89 ± 7.04 Nm to −17.61 ± 6.81 Nm after training (p = 0.043). The dorsiflexion AROM increased from 5.58 ± 13.18° to 15.97 ± 11.21° (p = 0.028). The proprioceptive acuity showed a trend of decline to 3.08 ± 2.07° in dorsiflexion and to −2.59 ± 1.94° in plantar flexion (p > 0.05). The RAT is a promising intervention for children with CP to improve sensorimotor functions of the lower extremities. It provided an interactive and motivating training to engage children with CP in rehabilitation to improve clinical and sensorimotor performance.
TAROT: Robotic observatories for gamma‐ray bursts and other sources

TAROT (Telescopes a Action Rapide pour les Objets Transitoires) are two robotic observatories designed to observe the early optical counterpart of gamma-ray bursts (GRBs) sources. As GRBs do not occur often, we use TAROT to observe other celestial targets: variable stars, minor-planets, supernovae, etc. In this paper we present the software tools presently used to manage the observations and to process and archive the data. We present also CADOR (Coordination et Analyse des Donnees des Observatoires Robotiques) which will centralize virtual observatory services associated to both TAROT telescopes. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Adaptive fractional window increment of TCP in multihop ad hoc networks

We propose an adaptive fractional window increasing algorithm (AFW) to improve the performance of the fractional window increment (FeW) in (Nahm et al., 2005). AFW fully utilizes the bandwidth when the network is idle, and limits the operating window when the network is congested. We evaluate AFW and compare the total throughput of AFW with that of FeW in different scenarios over chain, grid, random topologies and with hybrid traffics. Extensive simulation through ns2 shows that AFW obtains 5% higher throughput than FeW, whose throughput is significantly higher than that of TCP-Newreno, with limited modifications.
New activation functions for complex-valued neural network

This paper presents a new types of complex-valued sigmoid function for a fully multi-layered complex-valued neural network (CVNN). By using the concept of the subordination between analytic functions in open disc, we able to study the reducibility of CVNN. A real-world problem example has been used as a classifier. The simulations results reveal that the proposed fully complex-valued network, been better trained reduces the testing time by 54% compared to the choice of using the traditional sigmoid activation function. Key words: Complex valued neural network, activation functions, reducibility, irreducibility, subordination.
Drug resistance mechanism of kinase inhibitors in the treatment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer, and it usually occurs following chronic liver disease. Although some progress has been made in the treatment of HCC, the prognosis of patients with advanced HCC is not optimistic, mainly because of the inevitable development of drug resistance. Therefore, multi-target kinase inhibitors for the treatment of HCC, such as sorafenib, lenvatinib, cabozantinib, and regorafenib, produce small clinical benefits for patients with HCC. It is necessary to study the mechanism of kinase inhibitor resistance and explore possible solutions to overcome this resistance to improve clinical benefits. In this study, we reviewed the mechanisms of resistance to multi-target kinase inhibitors in HCC and discussed strategies that can be used to improve treatment outcomes.
The Application and Research of New Digital Technology in Marine Aquaculture

Marine aquaculture has become an important strategy to enable the ecological and sustainable development of fishery due to the decreasing natural fishery resources. To solve farming pain points, improve farming efficiency and modernize fisheries, new digital technologies, such as the Internet of Things, big data, cloud computing, artificial intelligence and blockchain, are increasingly being widely applied in aquaculture. This paper introduces the interrelationship of new digital technologies and the framework of their application in marine aquaculture. The results of the application of each new digital technology in marine aquaculture are highlighted, and the advantages or problems of each new digital technology in marine aquaculture are pointed out. Further, the application of new digital technologies in deep-sea aquaculture facilities is enumerated. Finally, the main problems faced by new digital technologies in the process of marine aquaculture production and the future development trend are sorted out and summarized to provide scientific reference for promoting the wide application of new digital technology in marine aquaculture.
Improving Speech Recognition Performance in Noisy Environments by Enhancing Lip Reading Accuracy

The current accuracy of speech recognition can reach over 97% on different datasets, but in noisy environments, it is greatly reduced. Improving speech recognition performance in noisy environments is a challenging task. Due to the fact that visual information is not affected by noise, researchers often use lip information to help to improve speech recognition performance. This is where the performance of lip recognition and the effect of cross-modal fusion are particularly important. In this paper, we try to improve the accuracy of speech recognition in noisy environments by improving the lip reading performance and the cross-modal fusion effect. First, due to the same lip possibly containing multiple meanings, we constructed a one-to-many mapping relationship model between lips and speech allowing for the lip reading model to consider which articulations are represented from the input lip movements. Audio representations are also preserved by modeling the inter-relationships between paired audiovisual representations. At the inference stage, the preserved audio representations could be extracted from memory by the learned inter-relationships using only video input. Second, a joint cross-fusion model using the attention mechanism could effectively exploit complementary intermodal relationships, and the model calculates cross-attention weights on the basis of the correlations between joint feature representations and individual modalities. Lastly, our proposed model achieved a 4.0% reduction in WER in a −15 dB SNR environment compared to the baseline method, and a 10.1% reduction in WER compared to speech recognition. The experimental results show that our method could achieve a significant improvement over speech recognition models in different noise environments.
Rapid faunal colonization and recovery of biodiversity and functional diversity following eelgrass restoration

Seagrass meadows and their associated biodiverse assemblages have declined globally due to environmental and anthropogenic stressors. Restoration of these critical habitats has the potential to reverse coastal biodiversity loss. Here, we tested the role of patch size (which can affect recruitment, food availability, and/or predation) in driving faunal colonization in an eelgrass (Zostera marina) restoration trial in Sweden. Eelgrass shoots were transplanted in plots with different configurations (continuous vs. checkerboard patterns with three patch sizes), and we followed invertebrate colonization (biodiversity and functional diversity) during the first two growing seasons. We found rapid faunal colonization following the transplantation of eelgrass shoots in all plots with invertebrate densities reaching 50–80% of the reference meadow after only one growing season (3 months). After two growing seasons (15 months), the faunal density, biodiversity, and functional diversity were similar to the reference meadow, despite eelgrass density and biomass still being lower than the reference meadow. Biodiversity, functional diversity, and community structure were similar among the different planted plots, that is, there was no indication that patch size influenced faunal colonization. We therefore consider that smaller patches embedded within larger restoration plots can be as effective for promoting biodiversity as continuous patches, with reduced costs and fewer shoots required. We also noted high natural variability between years both in the reference meadow and planted plots, showing the dynamic nature of seagrass ecosystems, and the importance of a well‐planned monitoring scheme that considers the reference area and restored area within the same temporal scale.
Framing second language comprehensibility: Do interlocutors’ ratings predict their perceived communicative experience?

Abstract Comprehensibility has risen to the forefront of second language (L2) speech research. To date, research has focused on identifying the linguistic, behavioral, and affective correlates of comprehensibility, how it develops over time, and how it evolves over the course of an interaction. In all these approaches, comprehensibility is the dependent measure, but comprehensibility can also be construed as a predictor of other communicative outcomes. In this study, we examined the extent to which comprehensibility predicted interlocutors’ overall impression of their interaction. We analyzed data from 90 paired interactions encompassing three communicative tasks. Interactive partners were L2 English speakers who did not share the same native language. After each task, they provided self- and partner-ratings of comprehensibility, collaboration, and anxiety, and at the end of the interaction, they provided exit ratings of their overall experience in the interaction, communication success, and comfort interacting with their partner. We fit mixed-effects models to the self- and partner-ratings to investigate if those ratings changed over time, and we used the results to derive model-estimated predictors to be incorporated into regression models of the exit ratings. Only the self-ratings, including self-comprehensibility, were significantly associated with the exit ratings, suggesting a speaker-centric view of L2 interaction.
Wireless Body Area Network for Preventing Self-Inoculation Transmission of Respiratory Viral Diseases

This paper proposes an idea of Wireless Body Area Networks (WBANs) based on Bluetooth Low-Energy (BLE) standards to recognize and alarm a gesture of touching the face, and in effect, to prevent self-inoculation of respiratory viral diseases, such as COVID-19 or influenza A, B, or C. The proposed network comprises wireless modules placed in bracelets and a necklace. It relies on the received signal strength indicator (RSSI) measurements between the bracelet and necklace modules. The measured signal is cleared of noise using the exponential moving average (EMA). Next, we use a classification algorithm based on a Least-Squares Support Vector Machine (LSSVM) in order to detect facial touches. When the results of the classification indicate that the hand is moving toward the face, an alarm is sent through the neck module and the vibrator embedded in the wrist module is switched on. Based on the performed tests, it can be concluded that the proposed solution is characterized by high accuracy and reliability. It should be useful, especially for individuals who are regularly exposed to the risk of respiratory infections.
Heterologous prime-boost cellular vaccination induces potent antitumor immunity against triple negative breast cancer

Introduction Triple negative breast cancer (TNBC) is the most aggressive and hard-to-treat subtype of breast cancer, affecting 10-20% of all women diagnosed with breast cancer. Surgery, chemotherapy and hormone/Her2 targeted therapies are the cornerstones of treatment for breast cancer, but women with TNBC do not benefit from these treatments. Although the prognosis is dismal, immunotherapies hold significant promise in TNBC, even in wide spread disease because TNBC is infiltrated with more immune cells. This preclinical study is proposing to optimize an oncolytic virus-infected cell vaccine (ICV) based on a prime-boost vaccination strategy to address this unmet clinical need. Methods We used various classes of immunomodulators to improve the immunogenicity of whole tumor cells in the prime vaccine, followed by their infection with oncolytic Vesicular Stomatitis Virus (VSVd51) to deliver the boost vaccine. For in vivo studies, we compared the efficacy of a homologous prime-boost vaccination regimen to a heterologous strategy by treating 4T1 tumor bearing BALB/c mice and further by conducting re-challenge studies to evaluate immune memory responses in surviving mice. Due to the aggressive nature of 4T1 tumor spread (akin to stage IV TNBC in human patients), we also compared early surgical resection of primary tumors versus later surgical resection combined with vaccination. Results In vitro results demonstrated that immunogenic cell death (ICD) markers and pro-inflammatory cytokines were released at the highest levels following treatment of mouse 4T1 TNBC cells with oxaliplatin chemotherapy and influenza vaccine. These ICD inducers also contributed towards higher dendritic cell recruitment and activation. With the top ICD inducers at hand, we observed that treatment of TNBC-bearing mice with the influenza virus-modified prime vaccine followed by VSVd51 infected boost vaccine resulted in the best survival. Furthermore, higher frequencies of both effector and central memory T cells along with a complete absence of recurrent tumors were observed in re-challenged mice. Importantly, early surgical resection combined with prime-boost vaccination led to improved overall survival in mice. Conclusion Taken together, this novel cancer vaccination strategy following early surgical resection could be a promising therapeutic avenue for TNBC patients.
Using LC-MS/MS to Determine Salivary Steroid Reference Intervals in a European Older Adult Population

A number of steroids, including glucocorticoids and sex hormones, have been associated with neurodegenerative and cardiovascular conditions common in aging populations. The application of liquid chromatography tandem mass spectrometry (LC-MS/MS) steroid analysis offers an opportunity to conduct simultaneous multiplex steroid analysis within a given sample. In this paper, we describe the application of an LC-MS/MS steroid analysis method for the assessment of reference ranges of steroids in human saliva samples (200 µL) collected from older adults (age 50 years and above) enrolled in a European cohort investigating the risk for Alzheimer’s dementia. Saliva samples were prepared using supported liquid extraction (SLE) along with a calibration curve and analysed using a Waters I-Class UPLC (Ultra Performance Liquid Chromatography) and a Sciex QTrap 6500+ mass spectrometer. Mass spectrometry parameters of steroids were optimised for each steroid and a method for the chromatographic separation of 19 steroids was developed. Lower limits of quantitation (LLOQs), linearity and other method criteria were assessed. In total, data from 125 participants (500 samples) were analysed and assessed for reference ranges (64 male, 61 female). A total of 19 steroids were detected in saliva within the range of the method. There were clear diurnal patterns in most of the steroid hormones detected. Sex differences were observed for androstenedione (A4), testosterone (T), cortisone (E) and aldosterone (Aldo). In the first sample of the day, dehydroepiandrosterone (DHEA) was significantly higher in healthy volunteers compared to those with Alzheimer’s disease biomarkers. This LC-MS/MS method is suitable for the analysis of 19 steroids in saliva in adults.
The impact of technostress on organizational functioning

Research in recent years has shown that IT-enabled companies have higher productivity than their competitors. The new and latest technological solutions enrich the range of tools available to workers, ensuring that information is always available, communication is easier, and customers are better served. At the same time, these opportunities also create psycho-social pressures that strain workers’ working and private lives and can lead to further problems of techno-addiction. The study aims to investigate the relationships between the characteristics of technostress and their combined impact on trust within the organization between human-human and human-technology relationships. The quantitative study involved 531 respondents. Responses were analyzed using IBM SPSS 28 and IBM AMOS 27. The results show that there is undoubtedly a close relationship and a mutually generating effect between technostress characteristics, which substantially impact trust within the organization. However, trust is still stronger in personal relationships than in human-technology relationships. According to the respondents, the level of preparedness, technological knowledge, and expectations influence trust in the use of technology, which also affects performance and work-life balance. AcknowledgmentThis study is supported by the Research Centre at Faculty of Business and Economics (No. PE-GTK-GSKK A095000000-4) of University of Pannonia (Veszprém, Hungary).
Interactions of magnetic domain walls with twin and grain boundaries in orthoferrites

Twin and grain boundaries impede the motion of magnetic domain walls in the orthoferrites. Bubbles distort and collapse before it is possible to propagate them through twin boundaries and all but very low angle grain boundaries. A new experimental technique has been used to measure the coercivity of isolated defects in nearly perfect crystals. The coercivity measured is the minimum applied field required to force a planar domain wall past a defect. Models of the spin configurations near twin and grain boundaries in the presence and absence of magnetic domain walls have been developed to explain the observed coercivities.
Analysis of Dicke narrowing in wall-coated and buffer-gas-filled atomic storage cells

Spectral lineshape narrowing of atomic vapour emission in a bufferless, wall-coated absorption cell has been analysed using the same formalism developed to describe sub-Doppler linewidths, Dicke narrowing, in a buffered cell. Within this formalism lineshapes are generated using Monte Carlo techniques. Dramatic linewidth reductions in the bufferless cell, compared with the buffered cell, occur because of the high probability that Doppler shifts before and after a particular wall collision will cancel each other. The formalism described allows more physical insight than the classic one-dimensional box model previously invoked to explain spectra narrowing in bufferless, wall-coated cells. Additionally, this formalism reveals a correlation between post-collision velocities and intercollision times in the buffered cell resulting in modifications of the standard Dicke analysis of these cells.
Constrained length connectivity and survivable networks

Some problems related to constrained length connectivity are addressed in this paper. Let Sl(x, y) be the minimum number of vertices that should be removed to destroy all the paths of length at most l between two vertices x and y. Let Il(x, y) be the maximum number of such node-disjoint paths. We first focus on f(l, d), defined as the supremum of (Sl(x, y))/(Il(x, y)) taken over all graphs and all pairs of x, y separated by a distance d. One of the results shown in this paper states that this supremum is exactly equal to l + 1 − d when d ≥ ⌈⅔l + 1)⌉ and is at least constant when 2 ≤ d ≤ 2 + ⌊(l + 1)/3⌋. Some classes of two connected graphs satisfying path-length constraints are defined. Most of them describe survivable telecommunication networks. Relationships between flows and constrained length connectivity are addressed. We also study the minimum edge numbers of these two connected graphs. Some of their topological properties are presented. © 2000 John Wiley & Sons, Inc.
Dielectric/metal sidewall diffusion barrier for Cu/porous ultralow-k interconnect technology

With the acknowledged insufficiency of traditional Ta or TaN barriers, deposited by physical vapor deposition (PVD), in the Cu/porous ultralow-k intermetal dielectric integration, an amorphous hydrogenated SiC (a-SiC:H)/Ta bilayer sidewall diffusion barrier has been fabricated using 0.13 μm Cu/porous ultralow-k [Porous-SiLK (Proprietary product from Dow Chemical Corporation, USA), k∼2.2] single damascene process. The electrical tests show that the line-to-line leakage current and the electrical breakdown field (EBD) of samples with this a-SiC:H/Ta dielectric/metal bilayer structure are significantly improved compared to the conventional PVD multi-stacked Ta(N) sidewall barrier. This improvement is mostly due to surface roughness modification after the deposition of a-SiC:H film, which, in addition to being a good barrier to Cu diffusion, can effectively “seal” the weak points on the surface of porous low-k material that are responsible for the sidewall barrier failure.
Numerical study of a narrow-track single-pole head useful for GHz response and large field strength requirements

The narrow-track single-pole (SPT) write head recording field was investigated using 3-D eddy current transient finite element analysis. After validating the finite element model for the SPT head with a double-layered medium, head field time variations were studied for various cases. Results show that a large head field strength reaching B/sub s/ of head pole at track width of 100 nm and high frequency response of 2 GHz.