Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Ultrasonication on Membrane Structure and Flux Recovery for Whey Ultrafiltration

In this study, the effect of ultrasound irradiation on the flux recovery and fouling mitigation for the membranes made of the polysulfone by the phase inversion method were investigated. Two ultrasound irradiation regimes, including inside and outside the module, were chosen for this study. The experiments were conducted to investigate the effect of ultrasound irradiation on the membrane structure and cleaning. The ultrasound was irradiated in the frequency of 20 kHz and at the intensity of 25.5-127.4 W/cm2. When the membranes were irradiated directly out of the module, they may be damaged and the large holes were formed due to remaining in direct acoustic cavitation area. The flux recovery for the whey ultrafiltration process was increased with the increase of the irradiation time and the ultrasound intensity. The released energy which is the result of the cavitation threshold of bubbles indirectly may clean the foulant. During 60 min ultrasound irradiation, the flux recoveries were between 83-91% for membranes. At the probe distance of 1 cm from the module and after 20 min, the destruction or cracks in the membrane may be happened. The FE-SEM showed that the adjacent holes were connected and the crack was formed. The results for using the ultrasound for cleaning the fouled membranes showed that in the long distances, a large number of cavitation bubbles collapses before they reach to the membrane and in short distance, due to higher energy density, the produced acoustic and turbulence stream are increased and the membrane may be damaged.
Synthesis of Some New Pyrazolone‐Based Heterocycles Containing Sulphone Moiety Acting as α‐Glucosidase and α‐Amylase Inhibitors

Diverse pharmacological activities have been associated with pyrazole derivatives, which include several applications in the field of medicinal chemistry and pharmaceuticals. They have potent antitumor [1–3], antibacterial [4], and antifungal [5] activities. In addition, thiophene derivatives possess antimicrobial [6], antiinflammatory, analgesic [7], anti-hypertensive [8], diabetes mellitus [9], gonadotropin-releasing hormone antagonists [10], anti-protozoal [11], anti-inflammatory [12], antitumor [13], anti-allergic [14], and antifungal [15] activities, templates for serine protease inhibition [16], and alternate substrate inhibitors of cholesterol esterase [17]. Moreover, furan derivatives act as antiinflammatory [18], anti-tuberculosis [19,20], antitumor [21], antimicrobial, and antifungal [22] agents. The strategy of medicinal chemists in their research is to discover new chemical entities, which maximally resemble existing drugs with respect to key physicochemical and biological properties, with the knowledge that the quest for “drug-like” properties may indeed help achieve good pharmacokinetic and pharmacodynamic properties. Such drug-like properties include lipophilicity, polarity, size, and solubility, plus some biological properties such as no or low inhibition of cytochromes P450, no QT prolongation, metabolic stability, and absence of toxicophoric groups. Therefore, these considerable biological and pharmacological activities attracted a great deal of our attention to synthesize new heterocyclic systems containing a pyrazolone moiety. For this purpose, we performed a series of reactions using 4-(2-chloroacetyl)1,2-dihydro-2,3-dimethyl-1-phenylpyrazol-5-one (1) as a precursor for the versatile functionalized 1-[4-(1,2dihydro-1,5-dimethyl-2-phenyl-3-oxo-3H-pyrazol-4-yl)-2phenyl sulfonyl-1-ethanone (2), which is useful for the fulfillment of our objective via its reactions with a variety of reagents. The products were elucidated on the basis of elemental analysis, spectral data, and alternative synthesis. In continuation of our interest in the synthesis of a variety of heterocyclic systems containing azoles, thiophene, and furane-based heterocycles moiety from readily obtainable inexpensive starting materials, we
Security Analysis of the TSN Backbone Architecture and Anomaly Detection System Design Based on IEEE 802.1Qci

With the development of intelligent and connected vehicles, onboard Ethernet will play an important role in the next generation of vehicle network architectures. It is well established that accurate timing and guaranteed data delivery are critical in the automotive environment. The time-sensitive network (TSN) protocol can precisely guarantee the time certainty of the key signals of automotive Ethernet. With the time-sensitive network based on automotive Ethernet being standardized by the TSN working group, the TSN has already entered the vision of the automotive network. However, the security mechanism of the TSN protocol is rarely discussed. First, the security of the TSN automotive Ethernet as a backbone E/E (electrical/electronic) architecture is analyzed in this paper through the Microsoft STRIDE threat model, and possible countermeasures for the security of automotive TSNs are listed, including the security protocol defined in the TSN, so that the TSN security protocol and the traditional protection technology can form a complete automotive Ethernet protection system. Then, the security mechanism per-stream filtering and policing (PSFP) defined in IEEE 802.1Qci is analyzed in detail, and an anomaly detection system based on PSFP is proposed in this paper. Finally, OMNeT++ is used to simulate a real TSN topology to evaluate the performance of the proposed anomaly detection system (ADS). As a result, the protection strategy based on 802.1Qci not only ensures the real-time performance of the TSN but can also isolate individuals with abnormal behavior and block DoS (denial of service) attacks, thus attaining the security protection of the TSN vehicle-based network.
Dynamic Study of Intelligent Traffic Behaviour Based on Multiple Traffic Modes

With the rapid development of society, the traffic problem has become increasingly severe, and the traditional methods can no longer effectively solve the current social traffic behaviour problems. Although studies on the dynamics of human traffic behaviour based on traffic modes can effectively reveal the anomalies in traffic behaviour, few studies integrate intelligent traffic behaviour with multiple traffic modes. Based on the numerous traffic data of bike-sharing and ride-hailing in a Chinese city, this paper reveals the dynamic characteristics of various traffic behaviours in the city by combining spatiotemporal characteristics index and urban spatial structure with human traffic behaviour patterns. The experimental results show that the traffic behaviour of the town presents a double logarithmic power-law distribution in time characteristics, and there is a close interdependent dynamic relationship with the city’s spatial structure. The research in this paper can reveal the relationship between bimodal power-law distribution and spatial characteristics in complex systems and help solve social traffic problems effectively in social reality. Further research results can provide practical planning guidance for the behavioural integration of multiple traffic in smart cities.
Luminescent Silica-Based Nanostructures from in Vivo Iridium-Doped Diatoms Microalgae

A novel biotechnological approach to the preparation of Ir-doped luminescent silica-based nanostructures is proposed availing use of diatoms microalgae which generate highly nanostructured biosilica shells (frustules) by in vivo biomineralization of orthosilicic acid. After the in vivo incorporation of a phosphorescent organometallic complex (Ir-1) in Thalassiosira weissflogii diatom frustules (DFs), bulk functionalized phosphorescent silica-based nanostructures are obtained by isolation and proper ultrafine processing of Ir-1-doped DFs. High-resolution characterization reveals the presence of phosphorescent hybrid organic/inorganic clusters composed of biogenic silica NPs intimately trapped within the diatom organic residual matter. The biofactory strategy investigated herein can be a sustainable, cost-effective, and scalable route to transition metal-doped silica nanomaterials and can pave the way to a great variety of heavy-metal and rare-earth metal doped silica nanostructures, whose applications rang.
ER-Store: A Hybrid Storage Mechanism with Erasure Coding and Replication in Distributed Database Systems

In distributed database systems, as cluster scales grow, efficiency and availability become critical considerations. In a cluster, a common approach to high availability is using replication, but this is inefficient due to its low storage utilization. Erasure coding can provide data reliability while ensuring high storage utilization. However, due to the large number of coding and decoding operations required by the CPU, it is not suitable for some frequently updated data. In order to optimize the storage efficiency of the data in the distributed system without affecting the availability of the data, this paper proposes a data temperature recognition algorithm that can distinguish data tablets and divides data tablets into three types, cold, warm, and hot, according to the frequency of access. Combining three replicas and erasure coding technology, ER-store is proposed, a hybrid storage mechanism for different data types. At the same time, we combined the read-write separation architecture of the distributed database system to design the data temperature conversion cycle, which reduces the computational overhead caused by frequent updates of erasure coding technology. We have implemented this design on the CBase database system based on the read-write separation architecture, and the experimental results show that it can save 14.6%–18.3% of the storage space while meeting the efficient access performance of the system.
Ship Track Prediction Based on DLGWO-SVR

To improve the accuracy of ship track prediction, the improved Grey Wolf Optimizer (GWO) and Support Vector Regression (SVR) models are incorporated for ship track prediction. The hunting strategy of dimensional learning was used to optimize the move search process of GWO and balance exploration and exploitation while maintaining population diversity. Selection and updating procedures keep GWO from being stuck in locally optimal solutions. The optimal parameters obtained by modified GWO were substituted into the SVR model to predict ship trajectory. Dimension Learning Grey Wolf Optimizer and Support Vector Regression (DLGWO-SVR), Grey Wolf Optimized Support Vector Regression (GWO-SVR), and Differential Evolution Grey Wolf Optimized Support Vector Regression (DEGWO-SVR) model trajectory prediction simulations were carried out. A comparison of the results shows that the trajectory prediction model based on DLGWO-SVR has higher prediction accuracy and meets the requirements of ship track prediction. The results of ship track prediction can not only improve the efficiency of marine traffic management but also prevent the occurrence of traffic accidents and maintain marine safety.
All‐in‐One Iontronic Sensing Paper

Paper has been utilized as an ideal platform for chemical, biological, and mechanical sensing for its fibrous structures and properties in addition to its low cost. However, current studies on pressure‐sensitive papers have not fully utilized the unique advantages of papers, such as printability, cuttability, and foldability. Moreover, the existing resistive, capacitive, and triboelectric sensing modalities have long‐standing challenges in sensitivity, noise‐proofing, response time, linearity, etc. Here, a novel flexible iontronic sensing mechanism, referred to as iontronic sensing paper (ISP), is introduced to the classic paper substrates by incorporating both ionic and conductive patterns into an all‐in‐one flexible sensing platform. The ISP can then be structured into 2D or 3D tactile‐sensitive origamis only by the paper‐specific manipulations of printing, cutting, folding, and gluing. Notably, the ISP device possesses a device sensitivity of 10 nF kPa−1 cm−2, which is thousands of times higher than that of the commercial counterpart, a resolution of 6.25 Pa, a single‐millisecond response time, and a high linearity (R 2 > 0.996). Benefiting from the unique properties of the fibrous paper structures and its remarkable performances, the ISP devices hold enormous potential for the emerging human–machine interfaces, including smart packaging, health wearables, and pressure‐sensitive paper matrix.
Joint Design of Beamforming and Edge Caching in Fog Radio Access Networks

In this paper, we study a novel transmission framework based on statistical channel state information (SCSI) by incorporating edge caching and beamforming in a fog radio access network (F-RAN) architecture. By optimizing the statistical beamforming and edge caching, we formulate a comprehensive nonconvex optimization problem to minimize the backhaul cost subject to the BS transmission power, limited caching capacity, and quality-of-service (QoS) constraints. By approximating the problem using the l 0 -norm, Taylor series expansion, and other processing techniques, we provide a tailored second-order cone programming (SOCP) algorithm for the unicast transmission scenario and a successive linear approximation (SLA) algorithm for the joint unicast and multicast transmission scenario. This is the first attempt at the joint design of statistical beamforming and edge caching based on SCSI under the F-RAN architecture.
Botnet Attack Detection by Using CNN-LSTM Model for Internet of Things Applications

The Internet of Things (IoT) has grown rapidly, and nowadays, it is exploited by cyber attacks on IoT devices. An accurate system to identify malicious attacks on the IoT environment has become very important for minimizing security risks on IoT devices. Botnet attacks are among the most serious and widespread attacks, and they threaten IoT devices. Motionless IoT devices have a security weakness due to lack of sufficient memory and computation results for a security platform. In addition, numerous existing systems present themselves for finding unknown patterns from IoT networks to improve security. In this study, hybrid deep learning, a convolutional neural network and long short-term memory (CNN-LSTM) algorithm, was proposed to detect botnet attacks, namely, BASHLITE and Mirai, on nine commercial IoT devices. Extensive empirical research was performed by employing a real N-BaIoT dataset extracted from a real system, including benign and malicious patterns. The experimental results exposed the superiority of the CNN-LSTM model with accuracies of 90.88% and 88.61% in detecting botnet attacks from doorbells (Danminin and Ennio brands), whereas the proposed system achieved good accuracy (88.53%) in identifying botnet attacks from thermostat devices. The accuracies of the proposed system in detecting botnet attacks from security cameras were 87.19%, 89.23%, 87.76%, and 89.64%, with respect to accuracy metrics. Overall, the CNN-LSTM model was successful in detecting botnet attacks from various IoT devices with optimal accuracy.
Selenomethionine Improves Mitochondrial Function by Upregulating Mitochondrial Selenoprotein in a Model of Alzheimer’s Disease

Alzheimer’s disease (AD), the most common neurodegenerative disease in elderly humans, is pathologically characterized by amyloid plaques and neurofibrillary tangles. Mitochondrial dysfunction that occurs in the early stages of AD, which includes dysfunction in mitochondrial generation and energy metabolism, is considered to be closely associated with AD pathology. Selenomethionine (Se-Met) has been reported to improve cognitive impairment and reduce amyloid plaques and neurofibrillary tangles in 3xTg-AD mice. Whether Se-Met can regulate mitochondrial dysfunction in an AD model during this process remains unknown.In this study, the N2a-APP695-Swedish (N2aSW) cell and 8-month-old 3xTg-AD mice were treated with Se-Met in vitro and in vivo. Our study showed that the numbers of mitochondria were increased after treatment with Se-Met. Se-Met treatment also significantly increased the levels of NRF1 and Mfn2, and decreased those of OPA1 and Drp1. In addition, the mitochondrial membrane potential was significantly increased, while the ROS levels and apoptosis rate were significantly decreased, in cells after treatment with Se-Met. The levels of ATP, complex IV, and Cyt c and the activity of complex V were all significantly increased. Furthermore, the expression level of SELENO O was increased after Se-Met treatment. Thus, Se-Met can maintain mitochondrial dynamic balance, promote mitochondrial fusion or division, restore mitochondrial membrane potential, promote mitochondrial energy metabolism, inhibit intracellular ROS generation, and reduce apoptosis. These effects are most likely mediated via upregulation of SELENO O. In summary, Se-Met improves mitochondrial function by upregulating mitochondrial selenoprotein in these AD models.
The Extent of Seasonally Suitable Habitats May Limit Forage Fish Production in a Temperate Estuary

The sustained production of sufficient forage is critical to advancing ecosystem-based management, yet factors that affect local abundances and habitat conditions necessary to support aggregate forage production remain largely unexplored. We quantified suitable habitat in the Chesapeake Bay and its tidal tributaries for four key forage fishes: juvenile spotted hake Urophycis regia, juvenile spot Leiostomus xanthurus, juvenile weakfish Cynoscion regalis, and bay anchovy Anchoa mitchilli. We used information from monthly fisheries surveys from 2000 to 2016 coupled with hindcasts from a spatially interpolated model of dissolved oxygen and a 3-D hydrodynamic model of the Chesapeake Bay to identify influential covariates and construct habitat suitability models for each species. Suitable habitat conditions resulted from a complex interplay between water quality and geophysical properties of the environment and varied among species. Habitat suitability indices ranging between 0 (poor) and 1 (superior) were used to estimate seasonal and annual extents of suitable habitats. Seasonal variations in suitable habitat extents in Chesapeake Bay, which were more pronounced than annual variations during 2000–2016, reflected the phenology of estuarine use by these species. Areas near shorelines served as suitable habitats in spring for juvenile spot and in summer for juvenile weakfish, indicating the importance of these shallow areas for production. Tributaries were more suitable for bay anchovy in spring than during other seasons. The relative baywide abundances of juvenile spot and bay anchovy were significantly related to the extent of suitable habitats in summer and winter, respectively, indicating that Chesapeake Bay habitats may be limiting for these species. In contrast, the relative baywide abundances of juvenile weakfish and juvenile spotted hake varied independently of the spatial extent of suitable habitats. In an ecosystem-based approach, areas that persistently provide suitable conditions for forage species such as shoreline and tributary habitats may be targeted for protection or restoration, thereby promoting sufficient production of forage for predators. Further, quantitative habitat targets or spatial thresholds may be developed for habitat-limited species using estimates of the minimum habitat area required to produce a desired abundance or biomass; such targets or thresholds may serve as spatial reference points for management.
The Journey of Business Opportunity Evaluation: When and Why Does Opportunity Novelty Promote Vs. Inhibit Opportunity Adoption?

As a typical characteristic of entrepreneurial opportunities, novelty is essential for firms to establish and maintain a sustainable competitive advantage under the current complex and dynamic business environment. However, why is it that some entrepreneurs adopt novel opportunities but others do not. Little is known about the precise nature of cognitive evaluation for opportunity novelty. Drawing upon information processing theory and construal level theory (CLT), we propose that the effects of opportunity novelty on adoption decisions depend on entrepreneurs' construal level through which information is processed. We design an experiment and find partial support for our hypotheses. Results indicate that entrepreneurs using a low-level construal perceive more risk for opportunity novelty, which in turn decreases the possibility of opportunity adoption. Meanwhile, opportunity novelty also positively influences entrepreneurs' creativity perception, which in turn increases the possibility of opportunity adoption. But construal level does not play any role in this evaluation path. Taken together, the findings improve our understanding of “how entrepreneurs evaluate an opportunity based on its objective characteristics” by providing empirical insights into the cognitive information processing process from opportunity novelty to adoption. Additionally, we discuss implications for entrepreneurial practice and future research.
A Pilot Event-Related Potentials Study on Mechanisms Underlying a tDCS-Enhanced Food-Specific Response Inhibition Task for Patients With Binge Eating Disorder

Behavioural studies demonstrate alterations in cognitive functioning, particularly impaired response inhibition and increased attentional bias towards food in binge eating disorder (BED). This pilot study aimed to investigate the neurophysiological processing of a food-specific inhibition training combined with anodal transcranial direct current stimulation (tDCS) of the right dorsolateral prefrontal cortex (DLPFC) in 16 patients with BED (mean age = 38.6, mean BMI = 33.7 kg/m2). Patients performed a food-specific antisaccade task at baseline (T0) and in a cross-over design with verum vs. sham stimulation at T1 and T2. We investigated (i) event-related potentials (ERPs; N2, ERN and P3 amplitudes) while executing the task at baseline, (ii) whether baseline ERPs would predict task performance at T1 and T2 and (iii) associations between ERPs, eating disorder pathology and impulsivity at baseline. The mean amplitude of N2 was less pronounced in erroneous saccades (ES) than correct saccades (CS), whereas ERN and P3 mean amplitudes were more pronounced in ES. Moreover, the P3 mean amplitude of ES predicted the percentage of ES at both follow up-measurements irrespective of the applied stimulation (sham vs. verum). N2 in trials with correct saccades were negatively correlated with nonplanning trait impulsivity, while P3 in erroneous antisaccade trials was negatively correlated with food-related impulsivity. Overall, the findings of reduced ERN, enhanced P3 and N2 amplitude might be interpreted as difficulties in response inhibition towards food in individuals with BED. In particular, P3 predicts task outcome at follow-up and might represent a potential marker for inhibitory control processes.