Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Questionnaire with Fibromyalgia Patients Reveals Correlations among Type of Pain, Psychological Alterations, and Effectiveness of Non-Pharmacological Therapies

Fibromyalgia (FM) is a chronic pain syndrome with an unclear etiology. In addition to pain, FM patients suffer from a diverse array of symptoms and comorbidities, encompassing fatigue, cognitive dysfunction, mood disorders, sleep deprivation, and dizziness. Due to the complexity of FM, the diagnosis and treatment of it are highly challenging. The aim of the present work was to investigate some clinical and psychological characteristics of FM patients, and to uncover possible correlations with pharmacological and non-pharmacological therapies. We conducted a cross-sectional, questionnaire-based study aimed at evaluating pain, psychological traits, and the self-perceived effectiveness of pharmacological and non-pharmacological treatments in an Italian population of FM patients. Descriptive statistics, correlation, and inference analyses were performed. We found a prevalence of a neuropathic/nociplastic type of pain, which correlated with psychological traits such as anxiety, low mood, psychophysical discomfort, and the inability to relax. The pain type and psychological traits proved to play a role in determining the self-perceived effectiveness of therapeutic interventions. Patients revealed a better response to non-pharmacological therapies, particularly dietary interventions, relaxation techniques, and psychotherapy rather than pharmacological interventions. The sum of our data indicates that for better outcomes, the type of pain and psychological traits should be considered for tailor-made treatments considering non-pharmacological protocols as a complement to the use of drugs.
A Comparative Analysis between Efficient Attention Mechanisms for Traffic Forecasting without Structural Priors

Dot-product attention is a powerful mechanism for capturing contextual information. Models that build on top of it have acclaimed state-of-the-art performance in various domains, ranging from sequence modelling to visual tasks. However, the main bottleneck is the construction of the attention map, which is quadratic with respect to the number of tokens in the sequence. Consequently, efficient alternatives have been developed in parallel, but it was only recently that their performances were compared and contrasted. This study performs a comparative analysis between some efficient attention mechanisms in the context of a purely attention-based spatio-temporal forecasting model used for traffic prediction. Experiments show that these methods can reduce the training times by up to 28% and the inference times by up to 31%, while the performance remains on par with the baseline.
Benefits of Preconditioning Cattle under Stochastic Feedlot Performance

Abstract Preconditioning cattle, a management practice of preparing cattle for feedlots as well as following a vaccination protocol for common diseases, has been shown to add value to cattle by reducing disease incidence and severity, yet it is not universally adopted. We estimated the benefits to a beef system of preconditioning weaned calves versus not preconditioning under stochastic returns. Purchasing preconditioned calves makes economic sense, but market efficiency requires complete information of the health status of the cattle, feedlot performance, along with the right market mechanisms, which may not be available in all markets.
Enhancing Graph Routing Algorithm of Industrial Wireless Sensor Networks Using the Covariance-Matrix Adaptation Evolution Strategy

The emergence of the Industrial Internet of Things (IIoT) has accelerated the adoption of Industrial Wireless Sensor Networks (IWSNs) for numerous applications. Effective communication in such applications requires reduced end-to-end transmission time, balanced energy consumption and increased communication reliability. Graph routing, the main routing method in IWSNs, has a significant impact on achieving effective communication in terms of satisfying these requirements. Graph routing algorithms involve applying the first-path available approach and using path redundancy to transmit data packets from a source sensor node to the gateway. However, this approach can affect end-to-end transmission time by creating conflicts among transmissions involving a common sensor node and promoting imbalanced energy consumption due to centralised management. The characteristics and requirements of these networks encounter further complications due to the need to find the best path on the basis of the requirements of IWSNs to overcome these challenges rather than using the available first-path. Such a requirement affects the network performance and prolongs the network lifetime. To address this problem, we adopt a Covariance-Matrix Adaptation Evolution Strategy (CMA-ES) to create and select the graph paths. Firstly, this article proposes three best single-objective graph routing paths according to the IWSN requirements that this research focused on. The sensor nodes select best paths based on three objective functions of CMA-ES: the best Path based on Distance (PODis), the best Path based on residual Energy (POEng) and the best Path based on End-to-End transmission time (POE2E). Secondly, to enhance energy consumption balance and achieve a balance among IWSN requirements, we adapt the CMA-ES to select the best path with multiple-objectives, otherwise known as the Best Path of Graph Routing with a CMA-ES (BPGR-ES). A simulation using MATALB with different configurations and parameters is applied to evaluate the enhanced graph routing algorithms. Furthermore, the performance of PODis, POEng, POE2E and BPGR-ES is compared with existing state-of-the-art graph routing algorithms. The simulation results reveal that the BPGR-ES algorithm achieved 87.53% more balanced energy consumption among sensor nodes in the network compared to other algorithms, and the delivery of data packets of BPGR-ES reached 99.86%, indicating more reliable communication.
HELIUM REIONIZATION SIMULATIONS. I. MODELING QUASARS AS RADIATION SOURCES

We introduce a new project to understand helium reionization using fully coupled N-body, hydrodynamics, and radiative transfer simulations. This project aims to capture correctly the thermal history of the intergalactic medium as a result of reionization and make predictions about the Lyα forest and baryon temperature–density relation. The dominant sources of radiation for this transition are quasars, so modeling the source population accurately is very important for making reliable predictions. In this first paper, we present a new method for populating dark matter halos with quasars. Our set of quasar models includes two different light curves, a lightbulb (simple on/off) and symmetric exponential model, and luminosity-dependent quasar lifetimes. Our method self-consistently reproduces an input quasar luminosity function given a halo catalog from an N-body simulation, and propagates quasars through the merger history of halo hosts. After calibrating quasar clustering using measurements from the Baryon Oscillation Spectroscopic Survey, we find that the characteristic mass of quasar hosts is for the lightbulb model, and for the exponential model. In the latter model, the peak quasar luminosity for a given halo mass is larger than that in the former, typically by a factor of 1.5–2. The effective lifetime for quasars in the lightbulb model is 59 Myr, and in the exponential case, the effective time constant is about 15 Myr. We include semi-analytic calculations of helium reionization, and discuss how to include these quasars as sources of ionizing radiation for full hydrodynamics with radiative transfer simulations in order to study helium reionization.
Obtaining Medical Textiles Based on Viscose and Chitosan/Zinc Nanoparticles with Improved Antibacterial Properties by Using a Dielectric Barrier Discharge

This study aimed to obtain functional viscose textiles based on chitosan coatings with improved antibacterial properties and washing durability. For that reason, before functionalization with chitosan/zinc nanoparticles (NCH+Zn), the viscose fabric was modified by nonthermal gas plasma of dielectric barrier discharge (DBD) to introduce into its structure functional groups suitable for attachment of NCH+Zn. NCH+Zn were characterized by measurements of hydrodynamic diameter and zeta potential and AFM. DBD-plasma-modified and NCH+Zn-functionalized fabrics were characterized by zeta potential measurements, ATR-FTIR spectroscopy, the calcium acetate method (determination of content of carboxyl and aldehyde groups), SEM, breaking-strength measurements, elemental analysis, and ICP-OES. Their antibacterial activity was determined under dynamic contact conditions. In addition to SEM, the NCH+Zn distributions on viscose fabrics were also indirectly characterized by measuring their absorbent capacities before and after functionalization with NCH+Zn. Washing durability was monitored through changes in the zeta potential, chitosan and zinc content, and antibacterial activity after 1, 3, and 5 washing cycles. The obtained results showed that DBD plasma modification contributed to the simultaneous improvement of NCH+Zn sorption and antibacterial properties of the viscose fabric functionalized with NCH+Zn, and its washing durability, making it suitable for the production of high-value-added medical textiles.
“It Made Me Feel like Things Are Starting to Change in Society:” A Qualitative Study to Foster Positive Patient Experiences during Phone-Based Social Needs Interventions

Many healthcare organizations are screening patients for health-related social needs (HRSN) to improve healthcare quality and outcomes. Due to both the COVID-19 pandemic and limited time during clinical visits, much of this screening is now happening by phone. To promote healing and avoid harm, it is vital to understand patient experiences and recommendations regarding these activities. We conducted a pragmatic qualitative study with patients who had participated in a HRSN intervention. We applied maximum variation sampling, completed recruitment and interviews by phone, and carried out an inductive reflexive thematic analysis. From August to November 2021 we interviewed 34 patients, developed 6 themes, and used these themes to create a framework for generating positive patient experiences during phone-based HRSN interventions. First, we found patients were likely to have initial skepticism or reservations about the intervention. Second, we identified 4 positive intervention components regarding patient experience: transparency and respect for patient autonomy; kind demeanor; genuine intention to help; and attentiveness and responsiveness to patients’ situations. Finally, we found patients could be left with feelings of appreciation or hope, regardless of whether they connected with HRSN resources. Healthcare organizations can incorporate our framework into trainings for team members carrying out phone-based HRSN interventions.
Analyses of cool stars using molecular lines

M-dwarfs are the coolest type of hydrogen-burning stars, and three times as numerous as all other stars in the Galaxy combined. Thanks to their low masses, luminosities and surface temperatures, they are potentially the best targets for finding exoplanets capable of supporting life. A low surface temperature unfortunately also allows the formation of various molecules, which complicates spectroscopic analyses.In this work, the molecular lines of titanium oxide (TiO) and various atomic lines are analyzed in a high-resolution (R ~ 68000) UVES spectrum of the M-dwarf GJ 876, as well as very high-resolution (R ~ 120000) spectra of five M-dwarfs. The TiO linelist is evaluated in a theoretical study of the molecular model.Results of the molecular line analysis are found to be misleading in certain regions. The strong TiO bands below wavelengths of 7300 A indicate results incompatible with atomic lines at higher wavelengths. Instead, the TiO lines near 7700 A are preferred. The theoretical study of the molecule improved both the precision and accuracy of transition wavelengths, but could not improve results of the molecular line analysis.The incompatible results are believed to stem from inaccuracies in the molecular line haze. Analyses in the wavelength range 7600-8800 A are found to indicate consistent results, but residual accuracy problems cannot be excluded in the present analysis. Further study of M-dwarfs and improved modeling of TiO could resolve this issue, as well as lead to general improvements in the analyses of cool stars.
An Insight into Molecular Targets of Breast Cancer Brain Metastasis

Brain metastasis is one of the major reasons of death in breast cancer (BC) patients, significantly affecting the quality of life, physical activity, and interdependence on several individuals. There is no clear evidence in scientific literature that depicts an exact mechanism relating to brain metastasis in BC patients. The tendency to develop breast cancer brain metastases (BCBMs) differs by the BC subtype, varying from almost half with triple-negative breast cancer (TNBC) (HER2− ER− PR−), one-third with HER2+ (human epidermal growth factor receptor 2-positive, and around one-tenth with luminal subclass (ER+ (estrogen positive) or PR+ (progesterone positive)) breast cancer. This review focuses on the molecular pathways as possible therapeutic targets of BCBMs and their potent drugs under different stages of clinical trial. In view of increased numbers of clinical trials and systemic studies, the scientific community is hopeful of unraveling the underlying mechanisms of BCBMs that will help in designing an effective treatment regimen with multiple molecular targets.
Joint Motion Compensation and Distortion Correction for Maneuvering Target Bistatic ISAR Imaging Based on Parametric Minimum Entropy Optimization

Bistatic inverse synthetic aperture radar (Bi-ISAR) can obtain complementary information about moving targets and overcome the inherent imaging limitations of monostatic ISAR. However, the complex motion of maneuvering targets invalidates the assumption that the imaging projection plane (IPP) is constant in conventional Bi-ISAR imaging. The 2-D spatial variant phase errors would be induced. Moreover, the phase errors have a high-order form due to the time-varying bistatic angle and the high maneuvering characteristics of the target. Meanwhile, the linear geometric distortion induced by the bistatic configuration seriously challenges target identification and classification. In this article, we propose a novel method to compensate for the 2-D spatial variant phase errors and correct the geometric distortion simultaneously for Bi-ISAR imaging based on parametric minimum entropy optimization. First, the signal mode for a maneuvering target in the bistatic configuration is developed. Second, based on the developed signal model, we analyze the coupling relationship between the 2-D high-order spatial variant phase errors and the bistatic angle and establish a parametric minimum entropy optimization model for high-order spatial variant phase error compensation. Then, an efficient Broyden–Fletcher–Goldfarb–Shanno (BFGS) method is adopted to obtain the optimal solution of spatial variant coefficients. Finally, with the estimated optimal parameters, the integrated processing of 2-D spatial variant phase error compensation and distortion correction can be realized. This method can simultaneously obtain well-focused and restored Bi-ISAR images of maneuvering targets without selecting prominent scatterers. Experiments based on scattering point simulation data and electromagnetic data verify the effectiveness of the proposed method.
Fatigue and Fracture Resistance Testing of Polyether Ether Ketone (PEEK) Implant Abutments in an Ex Vivo Chewing Simulator Model

Polyether ether ketone (PEEK) has been introduced into implant dentistry as a viable alternative to current implant abutment materials. However, data on its physico-mechanical properties are still scarce. The present study sought to shed light on this topic utilizing an ex vivo chewing simulator model. A total of 48 titanium two-piece implants were allocated into three groups (n = 16 per group): (1) implants with PEEK abutments and an internal butt-joint connection (PBJ), (2) implants with PEEK abutments and an internal conical implant–abutment connection (PC), and (3) implants with zirconia abutments and an internal butt-joint connection (ZA). All abutments were restored with a non-precious metal alloy crown mimicking the upper right central incisor. A dynamic chewing simulation of half (n = 8) of the specimens per group was performed with 5 × 106 cycles and a load of 49 N at a frequency of 1.7 Hz with thermocycling between 5 and 55 °C. The other eight specimens served as unloaded controls. Surface roughness, implant–abutment connection microgaps (IACMs), and the titanium base–abutment interface microgaps (TAIMs) in the loaded groups were evaluated. Finally, a quasi-static loading test was performed in a universal testing machine with all samples to evaluate fracture resistance. Overall, 23 samples survived the artificial chewing process. One abutment screw fracture was observed in the PC group. The ZA group showed higher surface roughness values than PEEK abutments. Furthermore, ZA revealed lower TAIM values compared to PEEK abutments. Similarly, ZA was associated with lower IACM values compared to PBJ. Fracture loads/bending moments were 1018 N/704 N cm for PBJ, 966 N/676 N cm for PC, and 738 N/508 N cm for ZA, with no significant differences compared to the unloaded references. Artificial loading did not significantly affect fracture resistance of the examined materials. PEEK abutments were associated with better load-bearing properties than zirconia abutments, although they showed higher microgap values. PEEK abutments could, therefore, be feasible alternatives to zirconia abutments based on the present ex vivo findings resembling 20 years of clinical service.
Experimental Evaluation of Theoretical Impact Models for Seismic Pounding

ABSTRACT One of the identified consequences of the aftermath of strong quakes is that structural pounding may trigger substantial damage including the collapse of colliding structures. This situation is attributed to inadequate distance between the adjacent structures. In order to address this concern, various numerical and experimental studies were conducted simulating earthquake induced pounding using different models of impact force. In this study, shaking table tests were conducted to assess the impact of seismic pounding between steel frame structures under near-field and far-field earthquakes. Five theoretical pounding force models, namely: linear spring, linear viscoelastic, Hertz, non-linear viscoelastic and Hertzdamp models were employed to replicate the pounding force. Various components of the theoretical models such as contact element stiffness, coefficient of restitution and impact damping ratio were calculated using the experimental results. Comparing the results of the Experimental Impact force time history with the prediction outcomes showed that the models over-predicted the pounding response. However, the prediction outcomes were congruent with the experimental results. Lastly, the linear viscoelastic model generated the least variance and most accurate predicted results compared to the other models. Hence, it can be inferred from the data that among other models, linear viscoelastic is the most accurate model to be used for the testing of pounding response.
Extended slow dynamical regime close to the many-body localization transition

Many-body localization is characterized by a slow logarithmic growth of the entanglement entropy after a global quantum quench while the local memory of an initial density imbalance remains at infinite time. We investigate how much the proximity of a many-body localized phase can influence the dynamics in the delocalized ergodic regime where thermalization is expected. Using an exact Krylov space technique, the out-of-equilibrium dynamics of the random-field Heisenberg chain is studied up to L=28 sites, starting from an initially unentangled high-energy product state. Within most of the delocalized phase, we find a sub-ballistic entanglement growth $S(t)\propto t^{1/z}$ with a disorder-dependent exponent $z\ge1$, in contrast with the pure ballistic growth $z=1$ of clean systems. At the same time, anomalous relaxation is also observed for the spin imbalance $I(t) \propto t^{-\zeta}$ with a continuously varying disorder-dependent exponent $\zeta$, vanishing at the transition. This provides a clear experimental signature for detecting this non-conventional regime.
WATCHING SEQUEL MOVIE: THE ROLE OF CUSTOMER EXPERIENCE AND CUSTOMER SATISFACTION ON REPURCHASE INTENTION

As a rapid rising and development of technology, now days people have many alternative as preferences to look for entertainment, one of them is through movie industry. It cannot be denied that a cinema today starts to be crowdedly visited due to new movies which are really potential to attract customers attention as one of alternatives that can be chosen of all kinds of entertainments offered. Many kinds of movies have entered Indonesia’s market, there are two kinds of movies they are sequel movie or a continued plot movie and fin movie that is a movie with only one settlement. The also of this research are to analyze and discuss about the effect of customer experience towards repurchase intention through customer satisfaction. The technique of sample is non-probability sampling with judgmental sampling method. The samples are 220 people. Data analysis uses path analysis. The result of this study shows that there is a significant effect of customer experience towards repurchase intention through customer satisfaction.
Study of Optimality Criteria in Design of Experiments.

Abstract : This paper have rigorously studied various optimality criteria currently adopted by design specialists in choosing a best design for performing an experiment. These optimality criteria includes: G-optimality, D-optimality, L-optimality, E-optimality, S-optimality, (M,S)-optimality, PHI sub p-criteria, Universal optimality, type 1 and 2 criteria and Schur optimality. (Author)
Single-Snapshot Nested Virtual Array Completion: Necessary and Sufficient Conditions

We study the problem of completing the virtual array of a nested array with a single snapshot. This involves synthesizing a virtual uniform linear array (ULA) with the same aperture as the nested array by estimating (or interpolating) the missing measurements. A popular approach for virtual array synthesis involves completing a certain Hankel/Toeplitz matrix from partial observations, by seeking low-rank solutions. However, existing theoretical guarantees for such structured rank minimization (which mostly provide sufficient conditions) do not readily extend to nested arrays. We provide the first necessary and sufficient conditions under which it is possible to exactly complete the virtual array of a nested array by minimizing the rank of a certain Toeplitz matrix constructed using a single temporal snapshot. Our results exploit the geometry of nested arrays and do not depend on the source configuration or on the separation between sources.