Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Nodal Metastasis by the AMES Scoring System in Patients with Papillary Thyroid Cancer

Purpose: We assessed the prognostic value of AMES to determine the extent of surgery in PTC patients, and compared AMES score usefulness and accuracy with [F] FDG PET/CT. Methods: We conducted a review of data from a single center and a single surgeon, who treated 341 patients with PTC with total thyroidectomy and prophylactic bilateral CLN dissection at a tertiary referral center, Chungnam National University Hospital, between 2001 and 2012. Results: In multivariate analysis, the rate of CLN metastasis was considerably higher in PTC patients with the higher AMES score (odds ratio [OR], 1.718; 95% confidence interval [CI], 1.073∼2.752), higher SUV of the CLN (>0) (OR, 6.525; CI, 3.184∼13.371), higher SUV of the tumor (>4.3) (OR, 1.855; CI, 1.065∼3.231). Conclusion: The AMES score is helpful in deciding whether to perform a CLN dissection, as there is a strong association between the AMES score and CLN metastasis. This high predictive value of CLN metastasis can help determine the extent of PTC surgery while considering the cost and effort.
Neutron detection array based on stilbene scintillators

Neutron detectors are used extensively at almost every nuclear research facility world over. Their range of application covers nearly all the topics in basic and applied nuclear research: in nuclear structure, for decay studies and as ancillary detectors for powerful in-beam spectroscopy arrays; in nuclear reactions, for the identification of the reaction channels and reconstruction of the complete kinematics; in nuclear astrophysics, for determining the neutron emission probabilities; in nuclear technology, for nuclear data measurements and in-core/off-core monitors; in nuclear medicine, as radiation monitors and dosimeters and in material science, for neutron imaging techniques. Paradoxically, the improvements during the last decades in neutron detection techniques have been modest in comparison to other fields of nuclear instrumentation. Materials, techniques and electronics developed a few teens years ago are still the state of art in neutron detection. Experiments planned at number of facilities like GANIL/SPIRAL, GSI/FRS, INFN LNL Legnaro, Jyvaskyla, REX-ISOLDE, JINR/ACCULINNA require more efficient and sensitive neutron detectors. In decay spectroscopy, innovative neutron detector arrays are necessary for the challenging low yield βn and β2n experiments and crucial in in-beam experiments for the identification of nuclei in fusion-evaporation reactions with radioactive beams. For the very exotic and low production isotopic species, high efficiency neutron calorimeters based on gas position sensitive detectors could lead to really low energy resolution spectroscopy. In studies of an extremely neutron rich nuclei via nuclear reactions a neutron detection is needed for reconstruction of a complete kinematics of the reaction and the decay channels. In the latter studies a detector array for neutrons emitted in heavy ion induced reactions at low to intermediate energies DEMON modules based on liquid scintillator NE213 [1] has been frequently used. With the recent progress in computing technology, material science, digital electronics and data analysis, several fields in which the performance of existing and future neutron detection systems can be improved have been identified. In general these improvements are related to: • Detector construction and assembly. • Data acquisition and electronics. • Monte Carlo simulation codes as the standard and necessary tools for detector design and data analysis. Therefore, due to interesting problematic and importance of the neutron detection systems in experimental studies at world leading facilities, practical exercises devoted to neutron detectors and detection systems are proposed at ACCULINNA set-up.
Global Marketing: Importance of Human Resource and Supply Chain Risk Management to Build a Successful Company from Global Marketing Perspective

Global markets are expanding rapidly. The term global marketing has been in use only since the 1980s. Before that decade, international marketing was the term used most often to describe marketing activities outside one's domestic market. Global marketing is not just a new label for an old phenomenon; however, it also provides a new vision for international marketing. This paper mainly examines the organization's internal management to coordinate their work and achieve certain goals or targets. This paper not only illustrates the challenges of developing and upholding strong trust in global human resource management from global marketing perspectives, but also the challenges that highlight how global marketers manage their global supply chain risk management. While global marketers comprises of members across different locations, cultures, and time, the highlighted challenges are overcome via two communication behaviours, such as cross- cultural communication and computer-mediated, which study describes the communication behaviours that might boost trust in global human resource management which may lead company to success. In today's increasingly complex environment, risk adjusted supply chain management also focused in this research which can drive into improved financial performance and competitive advantage.
Sleep habits in children affected by autism spectrum disorders: A preliminary case-control study

FRANCESCO PRECENZANO*1, MARIA RUBERTO*2, LUCIA PARISI3, MARGHERITA SALERNO4, AGATA MALTESE3, DOMENICO VERDE1, GABRIELE TRIPI5,6, PALMIRA ROMANO1, ANNABELLA DI FOLCO3, TERESA DI FILIPPO3, GIOVANNI MESSINA7, MICHELE ROCCELLA3 1Clinic of Child and Adolescent Neuropsychiatry; Headache Center for children and adolescents, Department of Mental Health and Physical and Preventive Medicine, Second University of Naples, Italy 2Department of Medical-Surgical and Dental Specialties, Second University of Naples, Italy 3Department of Psychological, Pedagogical and Educational Sciences, University of Palermo, Italy 4Sciences for Mother and Child Health Promotion, University of Palermo, Italy 5Department PROSAMI, University of Palermo, Italy6Childhood Psychiatric Service for Neurodevelopmental Disorders, CH Chinon, France7Department of Experimental Medicine, Section of Human Physiology and Unit of Dietetics and Sports Medicine, Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
Critical care echocardiography and outcomes in the critically ill

Purpose of review Critical care echocardiography offers a comprehensive assessment of cardiac anatomy and function performed by the intensivist at point of care. This has resulted in widespread use of critical care echocardiography in ICUs leading to the question if this increased usage has resulted in improved patient outcomes. Recent findings Recent studies have evaluated the role of critical care echocardiography in the ICU with an emphasis on establishing accurate diagnosis and measurement of haemodynamic variables. There are no prospective randomized controlled trials that have examined the effect of critical care echocardiography on patient outcomes Summary Although the effect of critical care echocardiography on patient outcomes has not yet been established, its value as a diagnostic tool has been well demonstrated. We can only assume that its diagnostic capability leads to an improvement in patient outcomes.
Reproducible Molecularly Imprinted Piezoelectric Sensor for Accurate and Sensitive Detection of Ractopamine in Swine and Feed Products

This paper describes the development of a reproducible molecularly imprinted piezoelectric sensor for the accurate and sensitive detection of ractopamine (RAC) in swine and feed products. The synthesized molecularly imprinted polymer (MIP) was directly immobilized on the surface of a quartz crystal microbalance (QCM) Au chip as the recognition element. The experimental parameters in the fabrication, measurement and regeneration process were evaluated in detail to produce an MIP-based piezoelectric sensor with high sensing capability. The developed piezoelectric sensor was verified to perform favorably in the RAC analysis of swine and feed products, with acceptable accuracy (recovery: 75.9–93.3%), precision [relative standard deviation (n = 3): 2.3–6.4%], and sensitivity [limit of detection: 0.46 ng g−1 (swine) and 0.38 ng g−1 (feed)]. This portable MIP-based chip for the piezoelectric sensing of RAC could be reused for at least 30 cycles and easily stored for a long time. These results demonstrated that the developed MIP-based piezoelectric sensor presents an accurate, sensitive and cost-effective method for the quantitative detection of RAC in complex samples. This research offers a promising strategy for the development of novel effective devices used for use in food safety analysis.
Within and Between-Person Differences in Language Used Across Anxiety Support and Neutral Reddit Communities

Although many studies have distinguished between the social media language use of people who do and do not have a mental health condition, within-person context-sensitive comparisons (for example, analyzing individuals’ language use when seeking support or discussing neutral topics) are less common. Two dictionary-based analyses of Reddit communities compared (1) anxious individuals’ comments in anxiety support communities (e.g., /r/PanicParty) with the same users’ comments in neutral communities (e.g., /r/todayilearned), and, (2) within popular neutral communities, comments by members of anxiety subreddits with comments by other users. Each comparison yielded theory-consistent effects as well as unexpected results that suggest novel hypotheses to be tested in the future. Results have relevance for improving researchers’ and practitioners’ ability to unobtrusively assess anxiety symptoms in conversations that are not explicitly about mental health.
Give me Something Unknown: Incorporate Exploration Preference in Cognition into Recommender System

Recommender systems (RSs) make recommendation for users by capturing their preference from historical behaviors. However, emphasizing too much on the perspective of prediction precision leads to the problem of preference overfitting, which blockades the user from touching a wide range of new but potentially interesting items. Usually, it would be beneficial for the system to attempt suitable extensions beyond users' existing preferences already expressed in the recommender system. Traditional recommender systems concentrate much more on what a user had explored than what she/he is yet to explore. Too much attention to the precision of recommendation can lead to a preference overfitting problem. Users have the need for certain amount of extension based on the existing preference. In this paper, we investigate how novel items should be recommended given the user's preference which is modeled from her/his historical behaviors. Inspired by Wundt Curve, a famous law in cognition psychology field, we propose an idea of Personal Exploration Preference (PEP) model to capture the user preference from another perspective, the strength of aspiration to explore. Then we integrate PEP model into traditional recommendation algorithms. Finally,we experimentally evaluate the improvement of PEP model to traditional algorithms on HetRec2011 dataset. Experiment results show that, on the Top-N recommendation task, PEP model can effectively capture user preference of exploration and improve recommendation quality significantly.
Application of the filter plate microbial trap (FPMT), for cultivating thermophilic bacteria from thermal springs in Barguzin area, eastern Baikal, Russia

ABSTRACT Hot springs are regarded as treasury of valuable thermophiles. Like other bacteria, thermophiles are not easily cultivated using conventional culture methods. We used an advanced cultivation method, the filter plate microbial trap (FPMT), to isolate bacteria from thermal springs. In total, 184 isolates were obtained from five thermal springs using the FPMT and standard agar plate method, and their 16S rRNA gene sequences were analyzed. FPMT allowed us to obtain a culture collection that was larger, richer, and more novel than that obtained by standard cultivation. Seven novel species were obtained using the FPMT technique, whereas only one was isolated using a standard cultivation. We also found clear differences in the patterns of phylogenetic diversity and physiological properties between isolates from two cultivation methods. The results have encouraged us to apply the FPMT method in other extreme environments and offer further support for fostering the development of new cultivation methods. Graphical Abstract Filter plate microbial trap (FPMT) allows for the exchange of chemical compounds such as nutrients, metabolites, and signal molecules from the environment into the agar, mimicking the in situ environmental conditions.
Neuromagnetic Decoding of Simultaneous Bilateral Hand Movements for Multidimensional Brain–Machine Interfaces

To provide multidimensional control, we describe the first reported decoding of bilateral hand movements by using single-trial magnetoencephalography signals as a new approach to enhance a user’s ability to interact with a complex environment through a multidimensional brain–machine interface. Ten healthy participants performed or imagined four types of bilateral hand movements during neuromagnetic measurements. By applying a support vector machine (SVM) method to classify the four movements regarding the sensor data obtained from the sensorimotor area, we found the mean accuracy of a two-class classification using the amplitudes of neuromagnetic fields to be particularly suitable for real-time applications, with accuracies comparable to those obtained in previous studies involving unilateral movement. The sensor data from over the sensorimotor cortex showed discriminative time-series waveforms and time-frequency maps in the bilateral hemispheres according to the four tasks. Furthermore, we used four-class classification algorithms based on the SVM method to decode all types of bilateral movements. Our results provided further proof that the slow components of neuromagnetic fields carry sufficient neural information to classify even bilateral hand movements and demonstrated the potential utility of decoding bilateral movements for engineering purposes such as multidimensional motor control.
A Marine Isolate of Bacillus pumilus Secretes a Pumilacidin Active against Staphylococcus aureus

Producing antimicrobials is a common adaptive behavior shared by many microorganisms, including marine bacteria. We report that SF214, a marine-isolated strain of Bacillus pumilus, produces at least two different molecules with antibacterial activity: a molecule smaller than 3 kDa active against Staphylococcus aureus and a molecule larger than 10 kDa active against Listeria monocytogenes. We focused our attention on the anti-Staphylococcus molecule and found that it was active at a wide range of pH conditions and that its secretion was dependent on the growth phase, medium, and temperature. A mass spectrometry analysis of the size-fractionated supernatant of SF214 identified the small anti-Staphylococcus molecule as a pumilacidin, a nonribosomally synthesized biosurfactant composed of a mixture of cyclic heptapeptides linked to fatty acids of variable length. The analysis of the SF214 genome revealed the presence of a gene cluster similar to the srfA-sfp locus encoding the multimodular, nonribosomal peptide synthases found in other surfactant-producing bacilli. However, the srfA-sfp cluster of SF214 differed from that present in other surfactant-producing strains of B. pumilus by the presence of an insertion element previously found only in strains of B. safensis.
Institutional Trading and Hedge Fund Activism

This paper investigates the role of institutional trading in the emergence of hedge fund activism – an important corporate governance mechanism. We demonstrate that institutional sales raise a firm’s probability of becoming an activist target. Further, by exploiting the funding circumstances of individual institutions, we establish that such effects occur through a liquidity channel – the activist camouflages his purchases among other institutions’ liquidity sales. Additional evidence supports our conclusion. First, activist purchases closely track institutional sales at the daily frequency. Second, such synchronicity is stronger among targets with lower expected monitoring benefits, suggesting that gains from trading with other institutions supplement these benefits in the activist’s targeting decision. Finally, we find that institutional sales accelerate the timing of a campaign at firms already followed by activists rather than attract attention to unlikely targets. Taken together, our findings offer a novel empirical perspective on the liquidity theories of activism; while activists screen firms on the basis of fundamentals, they pick specific targets at a particular time by exploiting institutional liquidity shocks.
An Unsupervised Compressed Sensing Algorithm for Multi-Channel Neural Recording and Spike Sorting

We propose an unsupervised compressed sensing (CS)-based framework to compress, recover, and cluster neural action potentials. This framework can be easily integrated into high-density multi-electrode neural recording VLSI systems. Embedding spectral clustering and group structures in dictionary learning, we extend the proposed framework to unsupervised spike sorting without prior label information. Additionally, we incorporate group sparsity concepts in the dictionary learning to enable the framework for multi-channel neural recordings, as in tetrodes. To further improve spike sorting success rates in the CS framework, we embed template matching in sparse coding to jointly predict clusters of spikes. Our experimental results demonstrate that the proposed CS-based framework can achieve a high compression ratio (8:1 to 20:1), with a high quality reconstruction performance (>8 dB) and a high spike sorting accuracy (>90%).
Improvements in pedestrian movement prediction by considering multiple intentions in a Multi-Hypotheses filter

Fully automated vehicles and mobile robots have to operate in a shared environment with pedestrians in the future. To minimize the risk for pedestrians, it is very important to track them in a precise way. One important information source is the intention of the pedestrian. For the integration of the intention information with conventional tracking algorithms, a Multi-Hypotheses filter is proposed, using a generalized potential field, which can be modeled using pedestrian movements. As the intention of the person is unknown, different hypotheses for the intention of the pedestrian are considered. The Multi-Hypotheses filter is used for the prediction of pedestrian trajectories and compared with a simple Kalman filter. The evaluation is performed in dependence on the free parameters, which are the prediction time, the tracking time and the measurement quality (modeled by additional additive white Gaussian noise). The proposed approach is evaluated using real camera data from a simple scenario in the Edinburgh Informatics Forum. For evaluation, the root mean square error and a confidence score, which is based on the normalized entropy, are considered. The Multi-Hypotheses based prediction outperforms the simple Kalman filter over the whole range of measurement quality, prediction and tracking time horizons in the case of the root mean square error and in the case of the confidence score.
Versatile Transition for Multilayer Compact Devices in Empty Substrate Integrated Waveguide

Empty substrate integrated waveguide (ESIW) devices can provide high quality and completely integrated devices, but they are usually larger than the same ones implemented with alternative technologies. One of the most extended strategies to compact electronic devices is the use of multilayer technology. Nevertheless, to perform multilayer devices in ESIW, a versatile and efficient transition between the guides in different layers is needed. Currently, only one multilayer device is known in this ESIW technology, which is a transition between a pair of guides built in contiguous layers that requires complex and nonstandard 3-D manufacturing processes. In this letter, a multilayer transition to connect a pair of guides separated by an arbitrary number of layers is successfully designed and experimentally validated without 3-D manufacturing processes. This novel and versatile transition opens the way to further develop multilayer compact devices in the ESIW technology such as compact filters.
Modeling User Quality of Experience of Olfaction-Enhanced Multimedia

Research on modelling user quality of experience (QoE) to date has primarily focused the combination of traditional media components; audio and video, or the individual influence of each. However, multisensory experiences have recently gained significant traction in the research community as a novel method to enhance QoE beyond what is possible with traditional media. This paper presents a model developed based on empirical data. It estimates user QoE of olfaction-enhanced multimedia. A set of 12 olfaction enhanced video clips were viewed by 84 assessors. A strong age and gender balance produced 6048 user ratings across six questions. Employing this dataset, the proposed model considers the influence of: system factors, user factors and content factors on user perceived QoE. The model is instantiated and validated. The analysis indicates that: content factors have a 10% influence on user QoE; age factors have an 11% influence; and gender factors have an 8% influence on user QoE. Also, content factors had the highest number of statistically significant influences across all of the factors evaluated. These results suggest that human, and content in addition to system factors play a key role in perceptual multimedia quality of olfaction enhanced multimedia. Further work is required to understand the remaining factors as well as the relationship between the media components has on QoE.
Spatial Frequency Loss for Learning Convolutional Autoencoders

This paper presents a learning method for convolutional autoencoders (CAEs) for extracting features from images. CAEs can be obtained by utilizing convolutional neural networks to learn an approximation to the identity function in an unsupervised manner. The loss function based on the pixel loss (PL) that is the mean squared error between the pixel values of original and reconstructed images is the common choice for learning. However, using the loss function leads to blurred reconstructed images. A method for learning CAEs using a loss function computed from features reflecting spatial frequencies is proposed to mitigate the problem. The blurs in reconstructed images show lack of high spatial frequency components mainly constituting edges and detailed textures that are important features for tasks such as object detection and spatial matching. In order to evaluate the lack of components, a convolutional layer with a Laplacian filter bank as weights is added to CAEs and the mean squared error of features in a subband, called the spatial frequency loss (SFL), is computed from the outputs of each filter. The learning is performed using a loss function based on the SFL. Empirical evaluation demonstrates that using the SFL reduces the blurs in reconstructed images.
A study of manual control with inching operation

インチング操作としては最も端的な形態と考えられるON/OFF切替えによる目標軌道のトレースを実験対象に選び, 主にD/C比を変えた場合のインチングに関する人間工学的基本特性を探る. 一連の実験を通じ, 連続的操作において従来からよく知られているD/C比に対するバスタブ曲線に準じる傾向がインチングにも存在するものの, インチングにはON状態持続時間制御とOFF状態持続時間制御ともいうべき2形態があることを見いだした. また, いずれのもとでもON/OFF切替え時の偏差に対する基準がインチングの成績に大きく影響していると思われ, それらの様子を探るべく, 別途に検証実験を行い, 基準に対するモデルの妥当性を確認した.