Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of main and total effect of PBPK parameters in Meningioma patients

This study aims to identify the most important parameters in the Physiologically-Based Pharmacokinetic (PBPK) model of Peptide Receptor Radionuclide Therapy (PRRT). By knowing the size of the contribution of physiological parameters to the PBPK model, it can reduce the variability of the absorbed dose (AD) in organs at risk, such as the kidney and tumor between individuals. The small variability has the potential to increase the accuracy of planning individual radionuclide therapy treatments. This study uses the extended Fourier Amplitude Sensitivity Test (eFAST) Global Sensitivity Analysis method, the best variance-based global method in analyzing the PBPK model. A whole-body PBPK model that has been developed for treatment planning in PRRT therapy for meningioma patients (n = 7). The parameters of interest analyzed were organ receptor densities Rdens, organ flows f, organ release rates, and peptide binding rate. AD as the desired output from the eFAST algorithm by calculating Si and STi from each AD Kidney and AD Tumor. All parameters of interest are converted into the lognormal distribution. The sampling strategy based on eFAST sampling, the interference factor is equal to 4. To see the convergence of the convergence value of Si and STi , a simulation was performed with a total evaluation of 129, 257, 513, 1025, 2049, 4097, and 8193. The results of the simulation, inter-individual variability of tumor AD (coefficient of variation CV up to CV = 73%) was higher than that organ at risk (e.g. kidneys CV around 22%). Based on GSA analysis, the most important parameter determined the AD of tumors, tumors receptor density (Si = 0.8, S Ti = 0.93), kidneys AD was kidneys receptor density (Si = 0.66, STi = 0.71). After validating Si by fixing every parameter considered important, the results can reduce the CV of the kidney AD from 22% to 1%, with a decrease in CV presentation of around 95%. CV AD tumor 1 was reduced by 68% from CV 44% to 14%, and CV in tumor AD 2 from 72% to 17% with a reduced CV presentation of about 77%. It was concluded that receptor measurement is important because it can improve the accuracy of radionuclide therapy treatment.
Cross-Corpus Speech Emotion Recognition Based on Joint Transfer Subspace Learning and Regression

Speech emotion recognition has become an attractive research topic due to various emotional states of speech signals in real-life scenarios. Most current speech emotion recognition methods are carried out on a single corpus. However, in practice, the training and testing data often come from different domains, e.g., different corpora. In this case, the model generalizability and recognition performance would decrease greatly due to the domain mismatch. To address this challenging problem, we present a transfer learning method, called joint transfer subspace learning and regression (JTSLR), for cross-corpus speech emotion recognition. Specifically, JTSLR performs transfer subspace learning and regression in a joint framework. First, we learn a latent subspace by introducing a discriminative maximum mean discrepancy (MMD) as the discrepancy metric. Then, we put forward a regression function in this latent subspace to describe the relationships between features and corresponding labels. Moreover, we present a label graph to help transfer knowledge from relevant source data to target data. Finally, we conduct extensive experiments on three popular emotional data sets. The results show that our method can outperform traditional methods and some state-of-the-art transfer learning algorithms for cross-corpus speech emotion recognition tasks.
Effects of high temperature on the mechanical behavior of calcium silicate hydrate under uniaxial tension and compression

When subjected to high temperatures, cement-based materials can dehydrate, which, in turn, affects the mechanical property of the main binding phase (calcium silicate hydrate) at the atomic scale. However, the effects of high temperature on the tensile and compressive behavior of calcium silicate hydrate (C−S−H) grains under uniaxial loading remains poorly understood. In this work, based on reactive molecular simulations, the tensile strength, compressive strength, and stress-strain relations of C−S−H grains with four calcium/silicon (C/S) ratios (1.10, 1.33, 164, and 1.80) both under and after (residual properties) high temperatures are investigated. It is shown that C−S−H grains can shrink due to the water loss induced by high temperature, and a low C/S ratio can lead to a thermo-stable molecular structure. Meanwhile, the residual tensile strength can be enhanced, particularly the tensile strength in the z-direction. Upon the residual compressive strength, in the x and y directions, high temperature can decrease the residual compressive strength for C/S = 1.10 or 1.33 but has no apparent effect for C/S = 1.64 or 1.80. While in the z-direction, the residual compressive strength can be enhanced due to the reduction in the interlayer space. In addition, high temperature can improve the residual tensile ductility but has no obvious effect on the residual compressive stress-strain relations. As for the mechanical properties under high temperature, both the tensile and compressive strengths can be weakened except that the tensile strength in the z-direction can undergo an increasing trend when the temperature is below 800 K due to significant shrinkage in the z-direction. Moreover, high temperature can make stress-strain curves exhibit good plasticity. Discussion indicates that the strength degradation of C−S−H gels or cement paste exposure to high temperatures is likely caused by the increasing porosity and coarsening of the void or defect size.
The Persistence Existence of Gossip in Social Media and Exchange Days to Determine Stock Return in the Indonesia Stock Exchange

It isn’t easy to define whether a stock return is determined by a certain factor or exchange day. There were many researches that proved that some influenced stock returns. There were also many researches gave facts that stock returns were caused by specific exchange days, such as week day effect. This research tries to track this logic. We tested the impact of gossips—thatspread out through social media—tostock return and persistence of theimpact. To anticipate the impact of exchange days, this research also included them as control variables. Multivariate statistic technique and combined with event study were used as analysis technique. The result suggests that the gossips in social media don’t show significance to influence the stock return, and no persistence to exist. The conclusion is that gossips in social media can’t be used to determine stock returns.
Evaluation of Antioxidant Activities, Oxidation Enzymes, and Quality of Nano-Coated Button Mushrooms (Agaricus Bisporus) during Storage

Agaricus Bisporus is an edible button mushroom that is highly perishable with an extremely short shelf-life at ambient temperature. This work aims to evaluate some antioxidant activities, oxidation enzymes, and determine postharvest qualities of nano-coated mushrooms with the combination of chitosan (CHN) component during storage at 4 °C for (0, 3, 6, 9, and 12 days). Silica/CHN Film strongly delayed the mushroom respiratory spike onset and blocked carbon dioxide passage from inside to the outside, while Titanium/CHN Film (0.035 mmol s−1 kg−1) established the lowest O2 production rate and thiobarbituric acid reactive substances production (6.21 nmol g−1). Silica/CHN Film was mainly effectual for the polyphenol contents (0.39 g kg−1) and antioxidant activities (78.14% and 71.09%) for DPPH and ABTS+ radical scavenging activities, respectively. The results reported that Silica/CHN Film induced the highest (catalase and ascorbate peroxidase) activities, while Titanium/CHN Film recorded the highest (peroxidase and superoxide dismutase) activities of antioxidant enzymes. Besides, Titanium/CHN Film preserved relatively lower contents of hydrogen peroxide (22.40 µmol g−1) and hydroxyl radical (0.16 µmol g−1). In a word, nano-materials used in coating films such as titanium or even silica with the combination of CHN can directly reduce the cell degradation, oxidation processes and enhance the harvested horticultural crops.
Is Innovation Redesigning District Heating? A Systematic Literature Review

The district heating (DH) industry has been characterized by continuous innovation for several decades, but there is limited knowledge on the characteristics of the sector’s innovation activities, arguably the most important information for understanding how the sector can continue to develop and further support the energy transition of society. We perform a systematic literature review (SLR) to identify the types of innovation, the levels of innovation and the relation between different innovations in the DH sector. A total of 899 articles are analyzed and coded into eight groups: fuel, supply, distribution, transfer, DH system, city system, impact and business. Most of the articles (68%) were identified in the groups: “supply”, “DH system,” and “impact”, with a focus on DH from a system or production perspective and its environmental impact. We find that there is limited research on DH firms” challenges, including management perspectives, such as asset management and customer focus. Despite this potential, we find only a limited number of articles related to innovation. Not much scholarly attention has been given to areas of large cost-saving, especially capital cost.
An integrated machine learning, noise suppression, and population-based algorithm to improve total dissolved solids prediction

Monitoring the water contaminants is of utmost importance in water resource management. Prediction of the total dissolved solid (TDS) is particularly essential for water quality management and planning in the areas exposed to a mixture of pollutants. TDS primarily includes inorganic minerals and organic matters, and various salts and increasing the concentration of TDS causes the esthetic problems. The reflection of the pollutant burden of the aquatic system can remarkably determined by TDS magnitudes. This study focuses on the prediction of TDS and several biochemical parameters such as Na, Ca, HCO3, and Mg in a river system. To overcome nonstationarity, randomness, and nonlinearity of the TDS data, a multi-step supervised machine learning evolutionary algorithm (MSMLEA) is proposed to improve the model's performance at two gaging stations, namely Rig-Cheshmeh and Soleyman-Tangeh, in the Tajan River, Iran. In addition, a hybrid model that recruits intrinsic time-scale decomposition (ITD) for frequency resolution of the input data as well as a multivariate adaptive regression spline (MARS) were adopted. A novel metaheuristic optimization algorithm, crow search algorithm (CSA), was also implemented to compute the optimal parameter values for the MARS model. To validate the proposed hybrid model, standalone MARS, empirical mode decomposition (EMD)-based models, and hybrid ITD-MARS as well as a MARS-CSA were considered as the benchmark models. Results suggest the ITD-MARS-CSA outperforms other models.
An Autosegmental Account of Melodic Processes in Jordanian Rural Arabic

This study aims at providing an autosegmental account of feature spread in assimilatory situations in Jordanian rural Arabic. I hypothesise that in any assimilatory situation in Jordanian rural Arabic the undergoer assimilates a whole or a portion of the matrix of the trigger. I also hypothesise that assimilation in Jordanian rural Arabic is motivated by violation of the obligatory contour principle on a specific tier or by spread of a feature from a trigger to a compatible undergoer. Data of the study were analysed in the framework of autosegmental phonology with focus on the notion of dominance in assimilation. Findings of the study have revealed that an undergoer assimilates a whole of the matrix of a trigger in the assimilation of /t/ of the detransitivizing prefix /Ɂɪt-/, coronal sonorant assimilation, and inter-dentalization of dentals. However, partial assimilation occurs in the processes of nasal place assimilation, anticipatory labialization, and palatalization of plosives. Findings have revealed that assimilation occurs when the obligatory contour principle is violated on the place tier. Violation is then resolved by deletion of the place node in the leftmost matrix and by right-to-left spread of a feature from rightmost matrix to leftmost matrix. It has been also revealed that spread of a primary or a non-primary feature from a trigger to an undergoer can motivate assimilation to occur in some assimilatory situations in Jordanian rural Arabic.
Bovine Paraoxonase-1 Activity in Oxidative Stress

Association of serum paraoxonase (PON) activity and oxidative stress in dairy cows as well as the relation between PON activity and HDL-c concentration were studied. A significantly lower PON and arylesterase (ARE) activities (P˂ 0.05) was found in cows with oxidative stress (parasitic and mastitic animals) compared to clinically healthy cows. Serum glutathione peroxidase (GPX) activity and malondialdehyde (MDA) level were also markedly reduced in cows with oxidative stress where as the serum HDL-c, LDL-c and cholesterol concentration showed significant reduction than the values in healthy cows. The results indicate a higher serum TAG and vLDL-c values in normal cows than in oxidative stress cases. The total protein content, albumin and globulin concentrations were showed slightly lower values in oxidative stress than in normal cows. A decrease serum PON activity may lead to reduction of anti oxidative protection during marked oxidative stress.
Validation of An Elbow Position Super-Twisting Sliding-Mode Controller for Upper-Limb Exosuit Using A Soft Position Sensor

Flexible exoskeletons, also known as exosuits, are robotic wearable devices intended to help healthy and unhealthy subjects in different tasks, such as daily life activities, load lifting or rehabilitation. A position control is required to assure stability and compliance in all assisted movements. In this paper, the authors propose the use of a flexible position sensor based on differential capacitance measurement as position feedback for the elbow joint in the flexible exoskeleton LUXBIT. This exosuit is controlled in position by a super-twisting sliding mode controller (SMC), which is robust against disturbances. Different movements involved in rehabilitation therapies are performed over three healthy subjects in order to evaluate the exosuit performance using this motion sensor. The measures given by the flexible sensor are compared to the ones obtained by OptiTrack motion capture system, which are used as ground truth.
Lung Contractive Change in Severe Acute Respiratory Failure Requiring Invasive Ventilation; A Comparison of Features Between Interstitial Lung Disease and Severe Infection

Background: Generally, the incidence of irreversible lung injury is considered to be higher in acute respiratory failure due to interstitial lung disease (ILD), compared to those due to severe infection. However, those sub-phenotypes, which follow irreversible lung injury, remain poorly characterized. We aimed to examine their clinical and radiological features, in patients who could not withdraw from ventilation after receiving any treatment (defined as“irreversible respiratory failure”). Methods: Retrospective study including all patients receiving CT evaluation at onset and invasive mechanical ventilation for severe infection or acute ILD, who admitted our institution from April 2013 to May 2019. Participants were divided into Infection group and ILD group according to the dominant cause, and predictors of irreversible respiratory failure were examined among those subjects. In addition, we quantitatively evaluated the changes in lung region volumes and dispersion of grand glass opacity, using automated methods. Results: 31 patients were subdivided to ILD group, whereas 139 patients were subdivided to Infection group. Significantly more subjects in ILD group developed irreversible respiratory failure (n=22; 70.9%), compared to those in Infection group (n=27; 19.4%; p<0.001). With validation of radiological features in those subjects, distinct CT findings, including lung contractive change and non-edematous lung injury (NE-LI), were found in both groups. Lung contractive change was observed with 23 subjects in ILD group (74.2%) and 7 subjects in Infection group (5.0%). Among those, >10% lung volume reduction was confirmed by CT analysis with 19 subjects in ILD group and 4 subjects in Infection group. By multivariate logistic regression analysis, the following factors were found to be strong predictors of irreversible respiratory failure; lung contractive change (odds ratio [OR]=32.6; 95% confidence interval [CI], 7.1-150), NE-LI suspicious lesion (OR=13.3; 95% CI [2.9-59]), ILD-dominant respiratory failure (OR=18.4; 95% CI, 4.3-79), multidrug-resistant bacterial- or fungal-infection (OR=6.4; 95% CI, 1.3-31). Conclusions: We demonstrated the presence of sub-phenotypes in acute respiratory failure due to ILD and severe infection, which followed an irreversible course with distinctive radiological features including lung contractive changes.
Statistical analysis of C–H activation by oxo complexes supports diverse thermodynamic control over reactivity

Transition metal oxo species are key intermediates for the activation of strong C–H bonds. As such, there has been interest in understanding which structural or electronic parameters of metal oxo complexes determine their reactivity. Factors such as ground state thermodynamics, spin state, steric environment, oxygen radical character, and asynchronicity have all been cited as key contributors, yet there is no consensus on when each of these parameters is significant or the relative magnitude of their effects. Herein, we present a thorough statistical analysis of parameters that have been proposed to influence transition metal oxo mediated C–H activation. We used density functional theory (DFT) to compute parameters for transition metal oxo complexes and analyzed their ability to explain and predict an extensive data set of experimentally determined reaction barriers. We found that, in general, only thermodynamic parameters play a statistically significant role. Notably, however, there are independent and significant contributions from the oxidation potential and basicity of the oxo complexes which suggest a more complicated thermodynamic picture than what has been shown previously.
Treatment of liquid swine manure in the sequencing batch reactor under aerobic and anoxic conditions

Laboratory studies were conductedon a sequencing batch reactor (SBR) for the treatmentof screenedliquid swine manure. The SBR was operated on the basis of a 24 hours cycle at 6 and 9 days hydraulic retention time and 20 days solids biological retention time. Nitrification and denitrification processes were carried out in the same reactor by alternating aerobic/anoxic conditions, and the tested time ratios were 19/3, 16/6, 14/8 and 10/12 (hours). The results from the overall performance indicated that above 99% NH3-N, 93% TKN, 97% COD and 97% TSS removal were achieved in the SBR treatment. Anoxic operation did not adversely affect the activity of the nitrifyers, and NO2-NO3-N concen tration increased up to 230 mg/L following air supply. However, sludge settling was poor in those reactors functioning with an anoxic period greater than 8 hours. As a result of nitrification and denitrification the removal of ammonia and nitrite plus nitrates nitrogen was 80 to 93%.
Achieving Privacy-Preserving and Lightweight Truth Discovery in Mobile Crowdsensing

To obtain reliable results from conflicting data in mobile crowdsensing, numerous truth discovery protocols have been proposed in the past decade. However, most of them do not consider the data privacy of entities involved (e.g., workers and servers), and several existing privacy-preserving truth discovery protocols either provide limited privacy protection or have heavy computation and communication overheads due to iterative computation and transmission over large ciphertexts. In this paper, we aim to propose privacy-preserving and lightweight truth discovery protocols to tackle the above problems. Specifically, we carefully design an anonymization protocol named AnonymTD to delink workers from their data, where workers’ data are computed and transmitted without complicated encryption. To further reduce each worker's overheads in the scenarios where workers are willing to share their weights, we resort to the perturbation technology to propose a more lightweight truth discovery protocol named PerturbTD. Based on workers’ perturbed data, two cloud servers in PerturbTD complete most of the workload of truth discovery together, which avoids the frequent involvement of workers. The theoretical analysis and the comparative experiments in this paper demonstrate that our two protocols can achieve our security goals with low computation and communication overheads.
Eliciting Individuals’ Financial Decision-Making Approaches with Verbal Protocols

How do individuals approach financial decisions? Do they apply sophisticated formulas, 'back of the envelope'-math, do they guess, or something completely different? We show that the verbal protocol method – i.e., having individuals explain their approaches – generates new insights to answer these questions. Our findings on approaches discovered are reliable within sample and have predictive power out of sample. Among other things, we find that when assessing the value of an annuity, 40% of individuals use some math, and some even use formulas similar to actuaries; the other 60% seem to guess. Valuation approaches used predict valuation outcomes and valuation precision, explain puzzling findings reported in earlier literature, and predict a behavioral reaction to an anchoring intervention designed to match one of the approaches discovered. The verbal protocol method opens new pathways to understand financial decision-making as well as to design effective policy interventions.
Design of High Speed and Low Power Approximate Multiplier for Image and Digital Signal Processing Applications

Truncation based approximate multiplier is a scalable multiplier in which truncation is performed based on the leading one bit positions in each and every input operands, hence the number of partial products are reduced. In this multiplier design the multiplication process is done by addition, shifting and multiplication processes which has a very good improvement in space occupation and power consumption when compared to the exact multiplier. To enhance the multipliers speed each and every input operand in the multiplication side are truncated using the method given below. Based upon the leading 1’s the input operands, the inputs are truncated show that the accuracy does not depend on input operand’s width. Hence this multiplier is scalable. Very large improvement in multiplier’s design parameters like power and area consumption are obtained which is independent of the width of the input operand. To find the working efficiency of this multiplier we have compared the design parameters with some recently proposed multipliers and the exact multiplier. They obtained result states that the proposed multiplier enhances power consumption, delay and area up to 90%, 80% and 95% when compared to be exact multiplier. Also our design outsmarts other multipliers in parameters like power consumption, speed and area. Proposed approximate multiplier has zero mean value Gaussian distribution. We have figured it out it by MATLAB applications and a good PSNR and MSE is obtained. The output shows that the degradation in quality is almost negligible. Also we recommend Truncation based approximate multiplier where power consumption has to be adjusted in multiplication operation.