Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Epoxidized Palm Oils Loading on the Crosslink Density and Rebound Resilience Characteristic of SBR Vulcanizates

The study about natural oils as processing aids in rubber was reported by several researchers for the past few years. The natural oils like rice bran oils, soybean oils, sunflower oils, vegetables oils and palm oils can be used as processing oils in rubber compounding [1-3]. These natural oils have been reported to have certain advantages compared to the petroleum based processing oils. In this study the potential of epoxidized palm oils (EPO) as additive and processing oils in carbon black filled styrene butadiene rubber was investigated. The main ingredients used were butadiene rubber (SBR), epoxidized palm oil (EPO) and carbon black. The vulcanized SBR rubber is then undergo several testing like swelling test, hardness and rebound resilience. An attempt was made to see whether the amount of EPO added to the SBR vulcanizates will affect the rebound resilience and swelling behaviour of the SBR vulcanizates. From this study, it was found that the compound contained higher EPO content tend to have lower rebound resilience, similar trend can be observed for hardness properties. While the crosslink density of the vulcanizates is decrease as the EPO content increases.
Frequency of Passive EHR Alerts in the ICU: Another Form of Alert Fatigue?

Objectives The intensive care unit (ICU) is a complex environment in terms of data density and alerts, with alert fatigue, a recognized barrier to patient safety. The Electronic Health Record (EHR) is a major source of these alerts. Although studies have looked at the incidence and impact of active EHR alerts, little research has studied the impact of passive data alerts on patient safety. Method We reviewed the EHR database of 100 consecutive ICU patient records; within, we assessed the number of values flagged as either as abnormal or “panic” across all data domains. We used data from our previous studies to determine the 10 most commonly visited screens while preparing for rounds to determine the total number of times, an abnormal value would be expected to be viewed. Results There were 64.1 passive alerts/patient per day, of which only 4.5% were panic values. When accounting for the commonly used EHR screens by providers, this was increased to 165.3 patient/d. Laboratory values comprised 71% of alerts, with the remaining occurring in vitals (25%) and medications (6%). Despite the high prevalence of alerts, certain domains including ventilator settings (0.04 flags/d) were rarely flagged. Conclusions The average ICU patient generates a large number of passive alerts daily, many of which may be clinically irrelevant. Issues with EHR design and use likely further magnify this problem. Our results establish the need for additional studies to understand how a high burden of passive alerts impact clinical decision making and how to design passive alerts to optimize their clinical utility.
Risk Factors for Recurrence After Treatment of N1b Papillary Thyroid Carcinoma

Objectives: To examine risk factors for posttreatment recurrence in papillary thyroid carcinoma (PTC) patients with initial presentation of lateral neck metastasis (N1b). Summary of Background Data: N1b PTC recurs after definitive treatment. Methods: Study subjects were 437 consecutive PTC patients who underwent total thyroidectomy and therapeutic neck dissection of central and lateral compartments and postoperative radioactive iodine ablation therapy. The patients’ demographics and pathological factors, including factors related to tumors and lymph nodes (LNs), and postoperative thyroglobulin levels were reviewed. Univariate and multivariate Cox proportional hazards regression analyses were used to identify factors associated with recurrence-free survival (RFS). Results: During a median follow-up of 83 months (range, 32–135 months), recurrence occurred in 81 (18.1%) patients. Univariate analyses showed that male sex, tumor size, macroscopic extrathyroidal extension, perineural invasion, extranodal extension, LN involvement, LN ratio, MACIS score, and postoperative serum levels of thyroglobulin were significantly associated with RFS (P < 0.05). Multivariate analyses revealed that LN ratio (> 0.25) in the lateral compartment (adjusted hazard ratio = 2.099, 95% confidence interval = 1.278–3.448; P = 0.003), and postoperative serum levels of stimulated (>5.0 ng/mL; 3.172, 1.661–6.056, P < 0.001) and unstimulated (>0.1 ng/mL; 3.200, 1.569–6.526, P = 0.001) thyroglobulin were independent predictors of any-site RFS. Clinical and tumor factors were not independent predictors of RFS outcomes (P > 0.1). Conclusions: Posttreatment recurrence is predicted by the LN ratio in the lateral compartment and postoperative serum levels of thyroglobulin in patients with metastatic PTC in the lateral neck.
A Survey on West Nile and Usutu Viruses in Horses and Birds in Poland

West Nile virus (WNV) and Usutu virus (USUV) are members of the family Flaviviridae which, natural life cycles involve mosquito–bird–mosquito transmission. Both represent emerging viruses in Europe with potential to cause neuroinvasive disease in humans. This study investigates the seroprevalence of serum neutralizing antibodies to WNV and to USUV in birds and in horses in Poland. Antibodies against WNV and USUV were detected in 5 (35.7%) and in 1 (7.14%) of 14 birds and in 62 (15.08%) and in 115 (27.98%) of 411 horses, respectively. Twenty-one WNV serologically positive horses (33.87%) and 67 USUV serologically positive horses (58.26%) did not travel outside Polish borders. Given the high abundance of potentially competent mosquito species in Poland, high populations of horses and different bird species, our findings highlight implementation of active control programs, including monitoring of geographic spread and dynamics of WNV and USUV transmission in both primary and accidental hosts. It is also important to improve public health awareness about the disease these viruses may cause.
Geostatistical motion interpolation

A common motion interpolation technique for realistic human animation is to blend similar motion samples with weighting functions whose parameters are embedded in an abstract space. Existing methods, however, are insensitive to statistical properties, such as correlations between motions. In addition, they lack the capability to quantitatively evaluate the reliability of synthesized motions. This paper proposes a method that treats motion interpolations as statistical predictions of missing data in an arbitrarily definable parametric space. A practical technique of geostatistics, called universal kriging, is then introduced for statistically estimating the correlations between the dissimilarity of motions and the distance in the parametric space. Our method statistically optimizes interpolation kernels for given parameters at each frame, using a pose distance metric to efficiently analyze the correlation. Motions are accurately predicted for the spatial constraints represented in the parametric space, and they therefore have few undesirable artifacts, if any. This property alleviates the problem of spatial inconsistencies, such as foot-sliding, that are associated with many existing methods. Moreover, numerical estimates for the reliability of predictions enable motions to be adaptively sampled. Since the interpolation kernels are computed with a linear system in real-time, motions can be interactively edited using various spatial controls.
Generalized Master–Slave-Splitting Method and Application to Transmission–Distribution Coordinated Energy Management

Transmission–distribution coordinated energy management (TDCEM) is recognized as a promising solution to the challenge of high distributed energy resource (DER) penetration, but there is a lack of a distributed computation method that universally and effectively works for the TDCEM. To bridge this gap, this paper presents a generalized master–slave-splitting (G-MSS) method. This method is based on a general-purpose transmission–distribution coordination model called G-TDCM, which enables the G-MSS to be applicable to most of the central functions of the TDCEM. In this G-MSS method, a basic heterogeneous decomposition (HGD) algorithm is first derived from the heterogeneous decomposition of the coupling constraints in the optimality conditions of the G-TDCM. Its optimality and convergence properties are proved. Then, inspired by the sufficient conditions for convergence, a modified HGD algorithm that utilizes the subsystem's response function is developed and demonstrated to converge faster. The distributed G-MSS method is then demonstrated to successfully solve a series of central functions of the TDCEM, e.g., power flow, contingency analysis, voltage stability assessment, economic dispatch, and optimal power flow. The severe issues of over-voltage and erroneous assessment of the system security that are caused by DERs are thus resolved by the G-MSS method with modest computation cost.
IFN-γ, IL-2, IP-10, and MIG as Biomarkers of Exposure to Leishmania spp., and of Cure in Human Visceral Leishmaniasis

New biomarkers are needed for monitoring the effectiveness of treatment for visceral leishmaniasis (VL). They might also improve the detection of the asymptomatic population in Leishmania-endemic areas. This paper examines the IL-2, IFN-γ, IFN-γ-induced protein 10 (IP-10), and monokine-induced-by-IFN-γ (MIG) levels in whole blood—stimulated in vitro with soluble Leishmania antigen (SLA)—taken from asymptomatic individuals and patients treated for VL living in a post-outbreak (Leishmania infantum) area in Spain, and in an endemic (Leishmania donovani) area of Bangladesh. IP-10 was found to be an accurate global marker of asymptomatic subjects with positive cellular/humoral tests, while MIG was found to be a better marker of contact with L. donovani than IL-2 but no for those with L. infantum. Determining IP-10, MIG, and IFN-γ levels proved useful in monitoring the cellular immune response following treatment for active disease caused by L. infantum.
Identification of different ALK mutations in a pair of neuroblastoma cell lines established at diagnosis and relapse

Anaplastic Lymphoma Kinase (ALK) is a transmembrane receptor kinase that belongs to the insulin receptor superfamily and has previously been shown to play a role in cell proliferation, migration and invasion in neuroblastoma. Activating ALK mutations are reported in both hereditary and sporadic neuroblastoma tumours, and several ALK inhibitors are currently under clinical evaluation as novel treatments for neuroblastoma. Overall, mutations at codons F1174, R1275 and F1245 together account for ∼85% of reported ALK mutations in neuroblastoma. NBLW and NBLW-R are paired cell lines originally derived from an infant with metastatic MYCN amplified Stage IVS (Evans Criteria) neuroblastoma, at diagnosis and relapse, respectively. Using both Sanger and targeted deep sequencing, this study describes the identification of distinct ALK mutations in these paired cell lines, including the rare R1275L mutation, which has not previously been reported in a neuroblastoma cell line. Analysis of the sensitivity of NBLW and NBLW-R cells to a panel of ALK inhibitors (TAE-684, Crizotinib, Alectinib and Lorlatinib) revealed differences between the paired cell lines, and overall NBLW-R cells with the F1174L mutation were more resistant to ALK inhibitor induced apoptosis compared with NBLW cells. This pair of cell lines represents a valuable pre-clinical model of clonal evolution of ALK mutations associated with neuroblastoma progression.
Mean-square stabilization for a class of discrete-time systems with random delay

This paper investigates the mean-square stabilization via output feedback for a networked linear time-invariant discrete time feedback system. The control signal is transmitted over a communication channel with multi-step random delay. It is assumed that the probability mass function of random delay steps is known and the sequence of random delay steps is an independent and identically distributed process. It is turned out from our previous results in mean-square stability of the system that this mean-square stabilization problem is a standard H2 optimal control problem. The resulting optimal controller which is determined by the transfer function of the system and stochastic properties of the random delay step process yields the largest stable margin for the closed-loop stochastic system in mean-square sense. The mean-square stabilizing controller is presented in terms of the solutions of two discrete algebraic Riccati equations (DAREs). In addition, a numerical example is given to illustrate the results in this work.
Energy-Spectral-Efficiency Analysis and Optimization of Heterogeneous Cellular Networks: A Large-Scale User-Behavior Perspective

Heterogeneous cellular networks (HCNs) are capable of meeting the explosive mobile-traffic demands. However, the conventional base station (BS) deployment strategy is unsuitable for supporting the often unpredictable nonuniform mobile-traffic demands, as governed by the large-scale user behavior (LUB). This results in the inefficient exploitation of the system's resources. In this paper, we develop an analytical framework for characterizing the achievable energy-spectral-efficiency (ESE) of HCNs, which explicitly quantifies the relationship between the network's ESE and the randomly time-varying LUBs as well as other network deployment parameters. Specifically, we model the quantitative impact of the geographical mobile-traffic intensity, the load migration factor, the users’ required service rate and the per-tier BS densities on the achievable ESE of the network, while considering the area-spectral-efficiency requirements. Importantly, a closed-form ESE expression is derived, which enables us to explicitly analyze the properties of the network's ESE. Furthermore, the optimal LUB-aware BS deployment strategy is proposed for maximizing the ESE under specific outage constraints. Using numerical simulations, we verify the accuracy of the analytical ESE expression and quantify the impact of several relevant system parameters on the achievable ESE. Furthermore, we evaluate the achievable ESE performance of the network under diverse time-varying LUB scenarios. Our work, therefore, provides valuable insights for designing future ultradense HCNs.
Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing

Social cognition is impaired in autism spectrum disorder (ASD). The ability to perceive and interpret affect is integral to successful social functioning and has an extended developmental course. However, the neural mechanisms underlying emotional face processing in ASD are unclear. Using magnetoencephalography (MEG), the present study explored neural activation during implicit emotional face processing in young adults with and without ASD. Twenty-six young adults with ASD and 26 healthy controls were recruited. Participants indicated the location of a scrambled pattern (target) that was presented alongside a happy or angry face. Emotion-related activation sources for each emotion were estimated using the Empirical Bayes Beamformer (pcorr ≤ 0.001) in Statistical Parametric Mapping 12 (SPM12). Emotional faces elicited elevated fusiform, amygdala and anterior insula and reduced anterior cingulate cortex (ACC) activity in adults with ASD relative to controls. Within group comparisons revealed that angry vs. happy faces elicited distinct neural activity in typically developing adults; there was no distinction in young adults with ASD. Our data suggest difficulties in affect processing in ASD reflect atypical recruitment of traditional emotional processing areas. These early differences may contribute to difficulties in deriving social reward from faces, ascribing salience to faces, and an immature threat processing system, which collectively could result in deficits in emotional face processing.
No effects of functional exercise therapy on walking biomechanics in patients with knee osteoarthritis: exploratory outcome analyses from a randomised trial

Aim To assess the effects of a functional and individualised exercise programme on gait biomechanics during walking in people with knee OA. Methods Sixty participants were randomised to 12 weeks of facility-based functional and individualised neuromuscular exercise therapy (ET), 3 sessions per week supervised by trained physical therapists, or a no attention control group (CG). Three-dimensional gait analyses were used, from which a comprehensive list of conventional gait variables were extracted (totally 52 kinematic, kinetic and spatiotemporal variables). According to the protocol, the analyses were based on the ‘Per-Protocol’ population (defined as participants following the protocol with complete and valid gait analyses). Analysis of covariance adjusting for the level at baseline was used to determine differences between groups (95% CIs) in the changes from baseline at follow-up. Results The per-protocol population included 46 participants (24 ET/22 CG). There were no group differences in the analysed gait variables, except for a significant group difference in the second peak knee flexor moment and second peak vertical ground reaction force. Conclusion While plausible we have limited confidence in the findings due to multiple statistical tests and lack of biomechanical logics. Therefore we conclude that a 12-week supervised individualised neuromuscular exercise programme has no effects on gait biomechanics. Future studies should focus on exercise programmes specifically designed to alter gait patterns, or include other measures of mobility, such as walking on stairs or inclined surfaces. Trial registration number ClinicalTrials.gov: NCT01545258.
Average 7T1R Nonvolatile SRAM With R/W Margin Enhanced for Low-Power Application

A new average 7T1R nonvolatile SRAM for low-power application is presented in this brief, which improves the read and write margin (RM/WM), as well as the restore energy, simply by using the source switch transistor. Simulation results demonstrate that the RM and WM will be improved by ~23% and ~73%, respectively, and the energy consumption will be decreased by ~63% for low-resistance state restoration, compared with the prior art initialization-and-overwrite-7T1R at nMOS typical corner and pMOS typical corner in Taiwan Semiconductor Manufacturing Company’s 65-nm technology. In addition, with the column-shared structure, the area penalty is cheerfully acceptable.
Mechanical Imaging of Soft Tissues With a Highly Compliant Tactile Sensing Array

Objective: The mechanical imaging of lumps in tissues via surface measurements can permit the noninvasive detection of disease-related differences in body tissues. We present and evaluate sensing techniques for the mechanical imaging of soft tissues, using a highly compliant electronic sensing array. Methods : We developed a mechanical imaging system for capturing tissue properties during automatic- or human-guided palpation. It combines extremely compliant capacitive tactile sensors based on soft polymers and microfluidic electrodes with custom electronic data acquisition hardware, and new algorithms for enhanced tactile imaging by reference to nominal tissue responses. Results: We demonstrate that the system is able to image simulated tumors (lumps), yielding accurate estimates of cross-sectional area independent of embedding depth. In addition, as a proof of concept, we show that similar tactile images can be obtained when the sensor is worn on a palpating finger. Conclusion: Soft capacitive sensors can accurately image lumps in soft tissue provided that care is taken to control and compensate for electrical and mechanical background signals. Significance: The results underline the utility of soft electronic sensors for applications in medical imaging or clinical practices of palpation.
Website Fingerprinting Defenses at the Application Layer

Abstract Website Fingerprinting (WF) allows a passive network adversary to learn the websites that a client visits by analyzing traffic patterns that are unique to each website. It has been recently shown that these attacks are particularly effective against . onion sites, anonymous web servers hosted within the Tor network. Given the sensitive nature of the content of these services, the implications of WF on the Tor network are alarming. Prior work has only considered defenses at the client-side arguing that web servers lack of incentives to adopt countermeasures. Furthermore, most of these defenses have been designed to operate on the stream of network packets, making practical deployment difficult. In this paper, we propose two application-level defenses including the first server-side defense against WF, as . onion services have incentives to support it. The other defense is a lightweight client-side defense implemented as a browser add-on, improving ease of deployment over previous approaches. In our evaluations, the server-side defense is able to reduce WF accuracy on Tor . onion sites from 69.6% to 10% and the client-side defense reduces accuracy from 64% to 31.5%.
Predators regulate prey species sorting and spatial distribution in microbial landscapes

The role of predation in determining the metacommunity assembly model of prey communities is understudied relative to that of interspecific competition among prey. Previous work on metacommunity dynamics of competing species has shown that sorting by habitat patch type and spatial patterning can be affected by disturbances. Microcosms offer a useful model system to test the effect of multi-trophic interactions and disturbance on metacommunity dynamics. Here, we investigated the potential role of predators in enhancing or disrupting sorting and spatial pattern among prey in experimental landscapes. We exposed multi-trophic protist microcosm landscapes with one predator, two competing prey, two patch resource types, and localized dispersal to three disturbance regimes (none, low, and high). Then, we used variation partitioning and spatial clustering analysis to analyse the results. In contrast with previous experiments that did not manipulate predators, we found that patch type did not structure prey communities very well. Instead, we found that it was the distribution of the predator that most strongly predicted the composition of the prey community. The predator impacted species sorting by (1) preferentially consuming one prey, thereby acting as a strong local environmental driver, and by (2) indirectly magnifying the impact of patch food resources on the less preferred prey. The predator also enhanced spatial signal in the prey community because of its limited dispersal. Our results indicate that predators can strongly influence prey species sorting and spatial patterning in metacommunities in ways that would otherwise be attributed to stochastic effects, such as dispersal limitation or demographic drift. Therefore, whenever possible, predators should be explicitly included as separate explanatory factors in variation partitioning analyses.