Miracle-dz/UniFAR-FTUs huggingface dataset:
Membrane Processes for Dye Wastewater Treatment: Recent Progress in Fouling Control

The textile industry generates large volumes of effluents on a daily basis, which contains substantial loads of organic compounds, inorganic salts, and suspended impurities. Membrane filtration has become an essential part of advanced treatment plants for dye wastewater treatment. Prevention of membrane fouling is one of the critical objectives for making the overall treatment process commercially viable. Development in this area during the past decade is critically evaluated in this review. Recent developments in the primary, secondary, and tertiary treatment steps in textile wastewater treatment are outlined. The methods employed for measuring, modeling, and understanding membrane fouling processes are discussed. Specific efforts toward fouling control by (a) pretreatment stages of textile wastewater and (b) modifying and optimizing the membrane separation process parameters such as feed composition, hydrodynamic conditions, and membrane properties are then assessed. Fouling related investigations for microfiltration/ultrafiltration membranes, membrane bioreactors, reverse osmosis, and nanofiltration membranes with special focus on textile wastewater treatment are discussed. Recent efforts toward developing new membranes and cleaning processes for fouled membrane activation are also discussed. Pilot plant studies involving membrane separation in combination with other treatment processes are also summarized. Strategies evolved and experiences gained from the industrial scale textile wastewater treatment plants in India are discussed. The authors also summarize the opportunities and the challenges remaining at different stages of industrial textile wastewater treatment units.
DRER: Deep Learning–Based Driver’s Real Emotion Recognizer

In intelligent vehicles, it is essential to monitor the driver’s condition; however, recognizing the driver’s emotional state is one of the most challenging and important tasks. Most previous studies focused on facial expression recognition to monitor the driver’s emotional state. However, while driving, many factors are preventing the drivers from revealing the emotions on their faces. To address this problem, we propose a deep learning-based driver’s real emotion recognizer (DRER), which is a deep learning-based algorithm to recognize the drivers’ real emotions that cannot be completely identified based on their facial expressions. The proposed algorithm comprises of two models: (i) facial expression recognition model, which refers to the state-of-the-art convolutional neural network structure; and (ii) sensor fusion emotion recognition model, which fuses the recognized state of facial expressions with electrodermal activity, a bio-physiological signal representing electrical characteristics of the skin, in recognizing even the driver’s real emotional state. Hence, we categorized the driver’s emotion and conducted human-in-the-loop experiments to acquire the data. Experimental results show that the proposed fusing approach achieves 114% increase in accuracy compared to using only the facial expressions and 146% increase in accuracy compare to using only the electrodermal activity. In conclusion, our proposed method achieves 86.8% recognition accuracy in recognizing the driver’s induced emotion while driving situation.
Harmonic Reflection Amplifier for Widespread Backscatter Internet-of-Things

The highly power-efficient backscattering communication scheme holds solid potentials to lead the Internet of Things technologies. However, the asymmetric radio frontend architectures that ensure cheap and pervasive communicating things and tags at one end of the link, overburden the other end of the link (“reader”) with complicated and expensive hardware. This turns out to prevent the integration of the technology in the wide spectrum of consumer electronic devices (e.g. RF smartphone platforms). By separating TX and RX frequency bands, the harmonic backscattering scheme drastically loosens the technological constraints toward integration. We propose here the use of a single tunnel diode to build a harmonic reflection amplifier (HRA), using the nonlinear behavior of the negative differential resistance region to both generate harmonics and amplify the signals. The circuit also behaves like a common backscatter, with the same-frequency backscattering modulation for operation with legacy readers. Operating below 150 mV, the HRA drains 144- $\mu \text{W}$ dc power with a measured positive conversion gain of 18 dB.
Active Collision Avoidance Strategy Considering Motion Uncertainty of the pedestrian

This work proposes an active collision avoidance between autonomous driving vehicle and pedestrian with motion uncertainty under urban road. A candidate trajectory planning method considering spatial and time sequences is proposed, which combines the polynomial path planning and the velocity planning with variable safety velocity. Then, a pedestrian-vehicle interaction model is constructed, which takes the pedestrian’s uncertain motion as a superposition of the Markov process without interference and the motion caused by the vehicle, and predicts the pedestrian’s motion probabilistically. On these bases, the optimal trajectory is evaluated from the candidate trajectories by safety, stability, and efficiency, as well as different driving styles. The proposed collision avoidance strategy is verified in conventional and emergency simulation scenarios. Simulation results show that it can effectively plan a safe, stable and efficient trajectory under normal and emergency conditions.
BENCHMARK CALCULATIONS WITH CORRELATED MOLECULAR WAVE FUNCTIONS. VII: BINDING ENERGY AND STRUCTURE OF THE HF DIMER

The hydrogen bond energy and geometry of the HF dimer have been investigated using the series of correlation consistent basis sets from aug‐cc‐pVDZ to aug‐cc‐pVQZ and several theoretical methods including Mo/ller–Plesset perturbation and coupled cluster theories. Estimates of the complete basis set (CBS) limit have been derived for the binding energy of (HF)2 at each level of theory by utilizing the regular convergence characteristics of the correlation consistent basis sets. CBS limit hydrogen bond energies of 3.72, 4.53, 4.55, and 4.60 kcal/mol are estimated at the SCF, MP2, MP4, and CCSD(T) levels of theory, respectively. CBS limits for the intermolecular F–F distance are estimated to be 2.82, 2.74, 2.73, and 2.73 A, respectively, for the same correlation methods. The effects of basis set superposition error (BSSE) on both the binding energies and structures have also been investigated for each basis set using the standard function counterpoise (CP) method. While BSSE has a negligible effect on the int.
Real-Time Expanded Field-of-View for Minimally Invasive Surgery Using Multi-Camera Visual Simultaneous Localization and Mapping

Minimally invasive surgery is widely used because of its tremendous benefits to the patient. However, there are some challenges that surgeons face in this type of surgery, the most important of which is the narrow field of view. Therefore, we propose an approach to expand the field of view for minimally invasive surgery to enhance surgeons’ experience. It combines multiple views in real-time to produce a dynamic expanded view. The proposed approach extends the monocular Oriented features from an accelerated segment test and Rotated Binary robust independent elementary features—Simultaneous Localization And Mapping (ORB-SLAM) to work with a multi-camera setup. The ORB-SLAM’s three parallel threads, namely tracking, mapping and loop closing, are performed for each camera and new threads are added to calculate the relative cameras’ pose and to construct the expanded view. A new algorithm for estimating the optimal inter-camera correspondence matrix from a set of corresponding 3D map points is presented. This optimal transformation is then used to produce the final view. The proposed approach was evaluated using both human models and in vivo data. The evaluation results of the proposed correspondence matrix estimation algorithm prove its ability to reduce the error and to produce an accurate transformation. The results also show that when other approaches fail, the proposed approach can produce an expanded view. In this work, a real-time dynamic field-of-view expansion approach that can work in all situations regardless of images’ overlap is proposed. It outperforms the previous approaches and can also work at 21 fps.
Anodic Passivation of Nickel in Sulfuric Acid Solutions

The potential decay curve of a passive nickel electrode on open circuit was followed in solutions of pH ranging from 0.4 to 1.4. The three arrest potentials observed in the decay curve correspond to the equilibrium potentials for the , , and the electrodes, respectively; the second potential is called the Flade potential, and the passivation occurs beyond this potential. A process for formation of the film is proposed that can be represented by the successive reactions, , . Then the critical potential beyond which the oxide formation takes place is calculated, under conditions when the solution in the vicinity of the surface becomes saturated with corresponding to the solubility product of , and is found to be equal to the Flade potential. The proposed mechanism can also explain the ability of the passive film to protect the metal against active dissolution due to breakdown of the film.The mechanisms of dissolution of nickel in the passive and overpassive potential regions are discussed from measurements of the Tafel constant and the pH dependence of the dissolution rate . The results are summarized as follows: passive region; .
On the quality control of ‘olive paste’, a specialty based on olives and olive oil

'Olive paste' is a preserved food gaining popularity as a gourmet product. Its quality depends on that of the major ingredients, table olives (green or black) and virgin olive oil, as well as on the changes occurring to the constituents of the latter during preparation and storage. In this view, our attention was focused on the characteristics of the lipid fraction (1.f.) of a great number of commercial products after a careful search in retail markets and the web. Ultraviolet absorbance values (K 232 , K 270 ) of the 1.f. , a criterion set for edible and non-edible olive oil oxidative status due to paste heat treatment during pasteurization, could not support the label information regarding the quality of the oil used. On the contrary, the content of α-tocopherol (∼250 mg/kg 1.f. or ∼50 mg/kg paste) was a strong indication of good-quality major ingredients. Within each brand, consistency with labeling was checked through squalene (higher content in products containing higher amounts of olive oil) or β-carotene determination (higher levels in preparations containing red pepper). For green olive paste samples, the values of the ratio pheophytin a/pyropheophytin a may be used to monitor the shelf life of the product. The findings support routine quality control of the new product.
Risk Stratification for Immediate Postoperative Hearing Loss by Preoperative BAER (Brainstem Auditory Evoked Response) and Audiometry in NF2-Associated Vestibular Schwannomas

Simple Summary Hearing preservation is one of the major goals in the surgical treatment of Neurofibromatosis Type 2 (NF2) associated vestibular schwannomas (VS) and hearing diagnostics are important monitoring parameters and intraoperative tools to pursue this goal. Our monocentric retrospective analysis aimed to predict postoperative hearing deterioration or loss based on preoperative audiometry and neurophysiological (brainstem auditory evoked potentials, BAEP) findings. In this respect and according to our data evaluation in 100 NF2-associated VS of 72 patients both parameters seem to be prognostic markers, particularly BAEP findings. Large discrepancies between both audiometry and BAEPs which were identified in twenty-one cases of our cohort appear to be at high risk of significant postoperative hearing worsening. Abstract Both brainstem auditory evoked potentials (BAEP) and audiometry play a crucial role in neuro-oncological treatment decisions in Neurofibromatosis Type 2 associated (NF2) vestibular schwannoma (VS) as hearing preservation is the major goal. In this study, we investigated the risk of immediate postoperative hearing deterioration (>15 dB and/or 15% loss in pure-tone average [PTA]/ speech discrimination score [SDS] in a cohort of 100 operated VS (ears) in 72 NF2 patients by retrospective analysis of pre- and postoperative hearing data (PTA, SDS, American Association of Otolaryngology–Head and Neck Surgery [AAO-HNS], and brainstem auditory evoked potential [BAEP] class) taking into account relevant influencing factors, particularly preoperative audiometry and BAEP status and the extent of resection. Immediately after surgery, the hearing was preserved in 73% of ears and approximately ~60% of ears kept their hearing classes. Preoperative BAEP (p = 0.015) and resection amount (p = 0.048) significantly influenced postoperative hearing outcome. The prediction model for postoperative hearing deterioration/loss between preoperative BAEP and AAO-HNS class showed increased risk by increasing BAEP class. Twenty-one tumors/ears were identified with large BAEP and AAO-HNS class discrepancies (≥2 points) and were associated with a high (48–100%) risk of deafness after surgery in ears with preoperative available hearing. Overall, the results were heterogeneous but the better both BAEP and audiometry class before surgery, the higher the chance of hearing maintenance afterwards. Large resection amounts (e.g., 100% risk in near-total resections) exhibit a significant (p < 0.05) higher risk compared to smaller amounts (e.g., 10/20% in laser-coagulated/partially resected tumors). Our results emphasized the indispensable role of both hearing monitoring in form of audiometry and neurophysiology (BAEP) in the pre-and perioperative monitoring of NF2-associated VS. Both BAEP and audiometry are good prognostic markers for the postoperative hearing outcome. The extent of resection should be strictly guided by and adjusted to the intraoperative neurophysiological monitoring.
Constrained Variable Projection Optimization for Stationary RBF-AR Models

Stationarity is fundamental for time-series modeling and prediction. In this article, we focus on the radial basis function network-based autoregressive (RBF-AR) models which have been widely used in practical applications. Compared to previous work, we give a less-restrictive sufficient condition for the asymptotic stationarity of the RBF-AR model. The parameter estimation of the RBF-AR model is converted to the optimization of a variable projection functional with constraints of stationarity to always derive a stationary model. The constrained evolutionary algorithm is used to solve the optimization problem. Numerical results demonstrate the effectiveness of the proposed method.
The role of angiogenetic single-nucleotide polymorphisms in thymic malignancies and thymic benign lesions

Background We previously showed that selected single-nucleotide-polymorphisms (SNPs) of genes involved in angiogenesis influence the aggressiveness of thymic epithelial tumors (TETs). This study analyzes their role in TETs and in thymic benign lesions, in order to investigate potential correlation with risk and outcome. Methods Genomic DNA was extracted from paraffin-embedded tissue of 92 patients, undergoing surgery at our Institution. We investigated by Real-Time PCR the SNPs of the following genes: platelet-derived growth factor receptor-α (PDGFRα), hypoxia-inducible factor-1α (HIF-1α), vascular endothelial growth factor A (VEGF-A), vascular endothelial growth factor receptor-2 and 3 (VEGF-2, VEGFR-3), excision repair cross-complementation group-1 (ERCC1). Results Fifty-seven TETs and 35 thymic benign lesions were included into the study. Frequency of SNPs was as follows: rs2057482 C, rs11158358 C and rs11549465 C polymorphisms of HIF1-a: thymomas < general population (P=0.008, P=0.007, and P=0.044 respectively). HIF1-a alleles: general population > study groups, rs1951795C SNP (P=0.026 for benign lesions and P=0.0007 for thymomas), rs10873142T SNP (P=0.008 and P=0.001 respectively), rs12434438 A SNP (P=0.034 and P=0.0007) and rs2301113A SNP (P=0.027 and P=0.010). rs699947C polymorphism of VEGF-A: benign lesions > general population (P=0.012). Conclusions This is the first study investigating the angiogenetic polymorphisms in thymic benign lesions and TETs. SNPs analysis may represent a further asset in identification of patients who could benefit from anti-angiogenetic therapy.
Silica-nanosphere-based organic–inorganic hybrid nanomaterials: synthesis, functionalization and applications in catalysis

The design and development of organic–inorganic hybrid nanomaterials and their applications in catalysis – an important area in sustainable chemistry – have captivated the attention of several researchers worldwide, as they enable environmentally friendly and benign catalytic processes. In recent years, novel approaches have been adopted to design highly selective nanostructured catalysts by controlling the interaction between the active catalytic species and the support material. There are extensive reports wherein silica nanoparticles (NPs) have been employed as solid supports for the fabrication of organic–inorganic hybrid nanocatalysts, possessing several outstanding features such as high activity and selectivity, excellent stability, efficient recovery and recyclability. Moreover, such quasi-homogeneous catalytic systems are free from diffusion problems that are generally associated with bulk catalytic systems, as these NPs can be dispersed in a wide range of organic solvents, eventually facilitating the accessibility of the substrates to the metal centres. This review attempts to summarise recent progress in the development of hybrid materials based on silica NPs, with special emphasis on the various fabrication strategies employed in previously published reports. Furthermore, a broad overview of the applications of these heterogeneous nanocatalysts in numerous organic transformations, including oxidation, reduction, condensation, amination, coupling, polymerization, addition and many more, is presented. It is believed that the successful applications of such versatile nanocatalytic systems would play a key role in establishing sustainable technologies.
Gouda Cheese with Modified Content of β-Casein as a Source of Peptides with ACE- and DPP-IV-Inhibiting Bioactivity: A Study Based on In Silico and In Vitro Protocol

In silico and in vitro methods were used to analyze ACE- and DPP-IV-inhibiting potential of Gouda cheese with a modified content of β-casein. Firstly, the BIOPEP-UWM database was used to predict the presence of ACE and DPP-IV inhibitors in casein sequences. Then, the following Gouda cheeses were produced: with decreased, increased, and normative content of β-casein after 1 and 60 days of ripening each (six variants in total). Finally, determination of the ACE/DPP-IV-inhibitory activity and the identification of peptides in respective Gouda-derived water-soluble extracts were carried out. The identification analyses were supported with in silico calculations, i.e., heatmaps and quantitative parameters. All Gouda variants exhibited comparable ACE inhibition, whereas DPP-IV inhibition was more diversified among the samples. The samples derived from Gouda with the increased content of β-casein (both stages of ripening) had the highest DPP-IV-inhibiting potency compared to the same samples measured for ACE inhibition. Regardless of the results concerning ACE and DPP-IV inhibition among the cheese samples, the heatmap showed that the latter bioactivity was predominant in all Gouda variants, presumably because it was based on the qualitative approach (i.e., peptide presence in the sample). Our heatmap did not include the bioactivity of a single peptide as well as its quantity in the sample. In turn, the quantitative parameters showed that the best sources of ACE/DPP-IV inhibitors were all Gouda-derived extracts obtained after 60 days of the ripening. Although our protocol was efficient in showing some regularities among Gouda cheese variants, in vivo studies are recommended for more extensive investigations of this subject.
Exploring Corporate Governance Mechanism on Intellectual Capital Disclosure: An Analysis of Indonesian Corporate Governance Forum

The purpose of this study is to analyze the effect of good corporate governance mechanisms consisting of the number of boards of directors, the proportion of independent commissioners, and the concentration of ownership on intellectual capital disclosures. The sampling method used was the purposive sampling method. This population research using financial company data listed in the Indonesian Corporate Governance Forum (FCGI) during 2017–2019 for a case study with a total sample of 300. In this study, hypothesis testing was carried out using partial least squares structural equation modeling (PLS-SEM). This study uses data processing with the application program WarpPLS 6.0. The findings of this research number of board of directors and ownership concentration have had a positive influence. However, the proportion of Independent Commissioners is unable to influence intellectual capital disclosure. Keywords: intellectual capital disclosure, corporate governance mechanism, corporate governance forum.
An Adaptive Symbol Decomposition With Serial Transmission for O-OFDM-Based VLC System

In this letter, an adaptive symbol decomposition with serial transmission (ASDST) scheme is proposed to reduce the effect of non-linear clipping noise for optical orthogonal frequency division multiplexing (O-OFDM) system in visible light communication. The transmitted O-OFDM symbol is adaptively decomposed by amplitude clipping and the decomposed symbols are fed into single light emitting diode (LED) by using serial framing. Adaptive symbol decomposition is the process of repeating the amplitude clipping according to each decomposition symbol amplitude and clipping levels. The simulation results show that the ASDST scheme offers improved transmission performance compared with conventional iterative signal clipping (ISC) scheme, since it eliminates all-zero symbols and transmits the same information with fewer decomposition symbols.
Phase Behavior and Polymorphism of Organic Crystals Confined within Nanoscale Chambers

Controlling polymorphism, the ability of a compound to adopt more than one solid-state structure, often relies on empirical manipulations of conditions such as solvent, temperature, and mode of crystallization. Despite a growing interest in nanocrystalline formulations, however, the influence of crystal size on polymorph formation and stability is largely unexplored. Nanocrystals of pimelic acid, HO2C(CH2)n-2CO2H (n = 7), glutaric acid (n = 5), suberic acid (n = 8), and coumarin (1,2-benzopyrone) in nanometer-scale pores of controlled pore glass (CPG) beads and hexagonally ordered cylindrical pores of poly(cyclohexylethylene) (p-PCHE) monoliths exhibit size-dependent polymorphism and thermotropic behavior because of the physical constraints imposed by the dimensions of the pores. Pimelic acid, suberic acid, and coumarin also exhibit heretofore unknown polymorphs, denoted δ-pimelic acid, β-suberic acid, and β-coumarin, in CPG with pore sizes <23 nm and p-PCHE with pore diameters <40 nm. The melting points .