Miracle-dz/UniFAR-FTUs huggingface dataset:
Partially acetylated cellulose nanofibrils from Agave tequilana bagasse and Pickering stabilization

Abstract Partially acetylated cellulose nanofibrils were obtained from the major residual stream associated with tequila production. The morphology and high cellulose content of the bagasse of Agave tequilana greatly facilitated deconstruction of such underutilized biomass. Mild chemical acetylation of the starting material afforded cellulose nanofibrils bearing surface ester groups, making the system less hydrophilic and plasticized. The acetylated nanofiber were characterized for morphology (atomic force microscopy), electrostatic charge (electrophoretic mobility), degree of substitution (DS) (titration) and main chemical features (infrared spectroscopy). Aqueous suspensions of the partially acetylated nanofibers (0.5% concentration) were mixed with a non-polar organic solvent (toluene) to obtain emulsions that were stable for at least 43 days. Cellulose nanofibrils of given DSs (different wettability) formed emulsions with different droplet size, thereby producing emulsion with different properties and stability. The cellulose nanofibrils with smaller sizes and higher contact angle (81°) generated small droplets (10–60 µm) while the cellulose nanofibrils with larger sizes and smaller water contact angle (40°) generated larger droplets (20–80 µm). Agave Bagasse CNF offers a great potential as Pickering emulsion stabilizers, which can be considered in the food, cosmetic and pharmaceutical fields. Graphical Abstract
Radial basis function neural network vibration control of a flexible planar parallel manipulator based on acceleration feedback

The self-excited vibration of flexible planar 3-RRR parallel manipulators is converted from the residual vibration after high-speed motion and is a resonance of the strongly coupled and nonlinear electromechanical system. This makes the active vibration control quite a challenging task. In this study, we attempt to adopt the radial basis function neural network control algorithm based on acceleration feedback for suppressing the self-excited vibration and guarantee its position accuracy. The stability of the controlled system is proved by the Lyapunov concept. Self-excited vibration control experiments are conducted near the singular region. Experimental results demonstrate the effectiveness of our adopted controller.
Impact of enzymatic treatment on wood surface free energy: contact angle analysis

Abstract The aim of this study was to investigate the effect of cellulase treatment on wood surface physicochemical characteristics. The cedar wood samples were treated by cellulase for 30 min at different concentrations: 0.2, 0.4, 0.6, 0.8, 1, and 1.2 mg/ml. Then the physicochemical properties (the wetting behavior and interfacial free energy) of the cedar samples surfaces were characterized by the sessile drop technique. The obtained results showed that the untreated cedar wood samples exhibited a hydrophobic character with a high water contact angle (θw = 71.9°) and a negative value of the interfacial free energy (∆Giwi = −59.3 mJ/m2). Thereafter, the wood hydrophobicity decreased continuously until it reached the hydrophilicity qualitatively (at the first concentration of cellulase (0.2 mg/ml)) and quantitatively (at 0.8 mg/ml of cellulase). The cedar wood surface treatment with cellulase also revealed a significant evolution of the acid-base parameters. Moreover, a linear relationship between the degree of hydrophobicity and the cellulase concentration has been found. This study clearly shows the impact that could have the produced enzyme by micro-organisms involved in wood biodegradation and especially their consequences on the physicochemical surface properties of the wooden materials.
Small and Vulnerable: Small Firm Productivity in the Great Productivity Slowdown

We provide broad-based evidence of a firm size premium of total factor productivity (TFP) growth in Europe after the Global Financial Crisis. The TFP growth of smaller firms was more adversely affected and diverged from their larger counterparts after the crisis. The impact was progressively larger for medium, small, and micro firms relative to large firms. It was also disproportionally larger for firms with limited credit market access. Moreover, smaller firms were less likely to have access to safer banks: those that were better capitalized banks and with a presence in the credit default swap market. Horseraces suggest that firm size may be a more important and robust vulnerability indicator than balance sheet characteristics. Our results imply that the tightening of credit market conditions during the crisis, coupled with limited credit market access especially among micro, small, and medium firms, may have contributed to the large and persistent drop in aggregate TFP.
An Efficient Deep Learning-Based Detection and Classification System for Cyber-Attacks in IoT Communication Networks

With the rapid expansion of intelligent resource-constrained devices and high-speed communication technologies, Internet of Things (IoT) has earned a wide recognition as the primary standard for low-power lossy networks (LLNs). Nevertheless, IoT infrastructures are vulnerable to cyber-attacks due to the constraints in computation, storage, and communication capacity of the endpoint devices. From one side, the majority of newly developed cyber-attacks are formed by slightly mutating formerly established cyber-attacks to produce a new attack tending to be treated as a normal traffic through the IoT network. From the other side, the influence of coupling the deep learning techniques with cybersecurity field has become a recent inclination of many security applications due to their impressive performance. In this paper, we provide a comprehensive development of a new intelligent and autonomous deep learning-based detection and classification system for cyber-attacks in IoT communication networks leveraging the power of convolutional neural networks, abbreviated as (IoT-IDCS-CNN). The proposed IoT-IDCS-CNN makes use of the high-performance computing employing the robust CUDA based Nvidia GPUs and the parallel processing employing the high-speed I9-Cores based Intel CPUs. In particular, the proposed system is composed of three subsystems: Feature Engineering subsystem, Feature Learning subsystem and Traffic classification subsystem. All subsystems are developed, verified, integrated, and validated in this research. To evaluate the developed system, we employed the NSL-KDD dataset which includes all the key attacks in the IoT computing. The simulation results demonstrated more than 99.3% and 98.2% of cyber-attacks’ classification accuracy for the binary-class classifier (normal vs anomaly) and the multi-class classifier (five categories) respectively. The proposed system was validated using k-fold cross validation method and was evaluated using the confusion matrix parameters (i.e., TN, TP, FN, FP) along with other classification performance metrics including precision, recall, F1-score, and false alarm rate. The test and evaluation results of the IoT-IDCS-CNN system outperformed many recent machine-learning based IDCS systems in the same area of study.
Pengaruh musim terhadap kelimpahan kumbang moncong (Coleoptera: Curculionidae) pada tipe penggunaan lahan berbeda di lanskap Hutan Harapan dan Taman Nasional Bukit Duabelas, Jambi

Perubahan fungsi tipe penggunaan lahan dari hutan menjadi perkebunan dapat menyebabkan hilangnya berbagai jenis keanekaragaman serangga, salah satunya adalah kelompok kumbang. Kumbang Curculionidae atau kumbang moncong merupakan salah satu famili terbesar dalam Ordo Coleoptera karena kemampuannya yang mampu beradaptasi di hampir semua habitat di alam. Penelitian ini bertujuan untuk mempelajari pengaruh musim terhadap kekayaan spesies dan kelimpahan individu kumbang moncong pada tipe penggunaan lahan perkebunan kelapa sawit dan karet di area lanskap Hutan Harapan dan Taman Nasional Bukit Duabelas, Jambi. Pengambilan sampel dilakukan pada musim kemarau dan musim hujan 2013–2014 dengan metode pengasapan menggunakan pestisida berbahan aktif piretroid. Pada setiap tipe penggunaan lahan (perkebunan kelapa sawit dan karet) ditentukan 4 plot pengamatan, dan masing-masing plot pengamatan ditentukan 3 titik sebagai subplot sehingga total keseluruhan terdapat 16 plot atau 48 subplot. Hasil penelitian menunjukkan bahwa ditemukan sebanyak 1.761 individu kumbang moncong yang terdiri atas 9 subfamili dan 45 morfospesies. Berdasarkan hasil analisis, perbedaan musim tidak memengaruhi kekayaan spesies dan kelimpahan individu, sedangkan perbedaan tipe penggunaan lahan hanya memengaruhi kelimpahan individu kumbang moncong. Berdasarkan hasil analisis kemiripan spesies Bray-Curtis menunjukkan sebesar 4% terjadi kemiripan spesies antar tipe penggunaan lahan, dan 46% kemiripan spesies antar musim. Hasil analisis indeks keanekaragaman pada tipe penggunaan lahan kelapa sawit lebih rendah dibandingkan dengan tipe penggunaan lahan karet. Salah satu spesies dominan yang ditemukan pada kedua tipe penggunaan lahan adalah Elaeidobius kamerunicus Faust. , juga ditemukan spesies spesifik yang hanya menempati tipe penggunaan lahan tertentu, seperti Rhynchophorus sp.01 hanya ditemukan pada tipe penggunaan lahan perkebunan kelapa sawit, dan Curculio sp.04 hanya ditemukan pada tipe penggunaan lahan karet.
Characterization of vertical GaN p–n diodes and junction field-effect transistors on bulk GaN down to cryogenic temperatures

There is great interest in wide-bandgap semiconductor devices and most recently in vertical GaN structures for power electronic applications such as power supplies, solar inverters and motor drives. In this paper the temperature-dependent electrical behavior of vertical GaN p–n diodes and vertical junction field-effect transistors fabricated on bulk GaN substrates of low defect density (104 to 106 cm−2) is described. Homoepitaxial MOCVD growth of GaN on its native substrate and the ability to control the doping in the drift layers in GaN have allowed the realization of vertical device architectures with drift layer thicknesses of 6 to 40 μm and net carrier electron concentrations as low as 1 × 1015 cm−3. This parameter range is suitable for applications requiring breakdown voltages of 1.2 kV to 5 kV. Mg, which is used as a p-type dopant in GaN, is a relatively deep acceptor (EA ≈ 0.18 eV) and susceptible to freeze-out at temperatures below 200 K. The loss of holes in p-GaN has a deleterious effect on p–n junction behavior, p-GaN contacts and channel control in junction field-effect transistors at temperatures below 200 K. Impact ionization-based avalanche breakdown (BV > 1200 V) in GaN p–n junctions is characterized between 77 K and 423 K for the first time. At higher temperatures the p–n junction breakdown voltage improves due to increased phonon scattering. A positive temperature coefficient in the breakdown voltage is demonstrated down to 77 K; however, the device breakdown characteristics are not as abrupt at temperatures below 200 K. On the other hand, contact resistance to p-GaN is reduced dramatically above room temperature, improving the overall device performance in GaN p–n diodes in all cases except where the n-type drift region resistance dominates the total forward resistance. In this case, the electron mobility can be deconvolved and is found to decrease with T−3/2, consistent with a phonon scattering model. Also, normally-on vertical junction field-effect transistors with BV = 1000 V and drain currents of 4 A are fabricated and characterized over the same temperature range. It is demonstrated that vertical GaN devices (diodes and transistors) utilizing p–n junctions are suitable for most practical applications including automotive ones (210 K < T < 423 K). While devices are functional at cryogenic temperatures (77 K) there may be some limitations to their performance due the freeze-out of Mg acceptors.
PENGUKURAN KINERJA SUPPLY CHAIN DENGAN PENDEKATAN METODE SCOR (SUPPLY CHAIN OPERATIONS REFERENCE) STUDI KASUS DI PT XYZ

Indonesia's non-migas industries will play a key role in improving economic impact for the country, as it is consistent with the gross domestic product (wb) of non-migas industries. In the meantime, there are some negative effects that are mitigated, one of which is to the environment, in which a company must be required to increase its corporate performance in order to keep up with the competition and still look at the impact of the environment. As for the method of supply chain management using scor approach methods. Because beyond getting a knowledge of the company's performance from the intermal process, measuring performance using company scor methods has also been able to recognize the company's environmental performance, it can also increase attention to a wide range of negaific impacts that would affect the life cycles of the company's xyz corporation, a packaged alcohol corporation that already has food and environmental security standards, Yet this company has never been able to consolidate green supphy chain management. The company's repairs on this study have yet to be determined by researchers measuring the kincing of the supply chain using scor method approaches, which, in turn, have been supported by ahp sound and value in standardization by snorm DE Boer to get more accurate results. From the calculations presented at trafic light, the company's performance of 89 31 means that the company's performance is good but there are 4 kpi units of 21 PI that fall in the red category which means that all four must be made in the red category With the cooperation of both verbal and non-verbal partners, socializing with their employees can also replace energy-efficient sensors. And exercised regular control over the raw materials and the correct scheduling flow of information and material flow.
New insight to niche partitioning and ecological function of ammonia oxidizing archaea in subtropical estuarine ecosystem

Abstract. Nitrification plays a central role in the estuarine nitrogen cycle. Previous studies in estuary mainly focused on the niche partition between ammonia-oxidizing archaea (AOA) and bacteria (AOB), while the diversity, activity, biogeography, and ecophysiology of different AOA groups remained unclear. Here, we for the first time report on niche partitioning and differentially distributed active populations among diverse AOA (inferred from amoA gene) in a typical subtropical estuary – Pearl River estuary (PRE). In the water column of the PRE, the AOA communities mainly consisted of water column A (WCA) and SCM1-like (Nitrosopumilus maritimus-like) sublineages. Surprisingly, we observed a strong disagreement in AOA communities at DNA and RNA levels. In DNA samples, WCA generally dominated the AOA community, and the distributional pattern indicated that WCA I and WCA II sublineages preferred oceanic and coastal conditions, respectively. In contrast, diverse SCM1-like sublineages were identified, and outnumbered WCA at RNA level, in which SCM1-like-III was limited to freshwater, while the rest of the sublineages were widely distributed in the estuary. The SCM1-like sublineages strongly correlated with nitrification rate, which indicated their important contribution to ammonia oxidation. Furthermore, intense nitrification contributed significantly to hypoxia conditions (nitrification contributed averaged 12.18 % of oxygen consumption) in the estuary. These results revealed different ammonia-oxidizing activities and niche partitioning among different AOA sublineages in estuarine water, which was unexplored in previous DNA and clone library-based studies. The ecological significance and functioning of the diverse AOA should be further explored in the marine ecosystem.
Large-Scale Linear Programming and Applications

Linear Programming has been used as an effective tool to solve a number of applications in manufacturing, transportation, military, healthcare, and finance. In a number of applications, the size of the formulation in terms of the number of variables and constraints can be quite large in order to accurately model practical systems. For example, Leachman (1993) formulates a linear programming model of over 150,000 variables and 100,000 constraints to solve a production planning problem for semiconductors at the Harris Corporation. With such large size problems, specialized procedures such as column generation, cutting planes, and the Dantzig-Wolfe decomposition may need to be employed to solve them. The purpose of this chapter is to provide an overview of these specialized procedures, and we conclude with an example of a large-scale formulation for solving a route balancing problem.
JPH203 as a potential L-Type Amino Acid Transporter 1 (LAT 1) inhibitor in the development of cancer theragnostic compounds

Background: Cancer has become a major cause of global health problems. Latest research currently focuses on an approach to cancer therapy that involves specific target molecules and theragnostic (therapy and diagnostic) agents. Among the specific target molecules in cancer therapy is LAT1, which is over expressed in cancer cells but under expressed in normal cells. Therefore, LAT1 inhibition can become an alternative to cancer therapy. A number of studies have shown that JPH203 specifically inhibits LAT1, thus reducing amino acid absorption into cancer cells and inhibiting cancer cell growth. Objective: The main objective of this literature study was to determine the potential of JPH203 as a LAT1 inhibitor to be developed into a novel theragnostic agent for cancer. Methods: Various studies were summarized to outline the development of JPH203 as a therapy targeting LAT1 and potential candidate of theragnostic compounds. Results: The results of the literature study showed that JPH203 as a selective LAT1 inhibitor was able to efficiently suppress the growth of cancer cells with a low IC50 value. Conclusion: The activity of LAT1 as an amino acid transporter of cancer cells could be selectively inhibited by JPH203, thereby allowing JPH203 to be reconsidered as a potential therapy in the development of theragnostic compounds against cancer. Keywords: JPH203, theragnostic, LAT1 inhibitor
Do Threats Galvanize Authoritarians or Mobilize Nonauthoritarians? Experimental Tests from 19 European Societies

Authoritarian predispositions and contextual threats are both thought to result in intolerance and prejudice towards immigrants and other minorities. Yet there is considerable dispute as to how authoritarianism and threat interact to produce an “authoritarian dynamic. ” Some scholars argue that threats increase intolerance by “galvanizing” authoritarians. Others claim that authoritarians are always intolerant toward outgroups, with threat instead “mobilizing” nonauthoritarians. Using experimental manipulations of immigrant cultural threat embedded in nationally representative samples from 19 European societies, this study offers a test of these competing hypotheses. While we find some evidence for the “galvanizing” hypothesis, we find no evidence for the “mobilizing” hypothesis. The effects vary considerably across national samples however, with immigrants from Muslim societies being particularly likely to activate authoritarian predispositions. These findings show how the migration of culturally distinctive groups has the potential to activate authoritarian dispositions, thereby pushing the issue of immigration to the center of political debates.
Impacts of long-range transport of aerosols on marine-boundary-layer clouds in the eastern North Atlantic

Abstract. Vertical profiles of aerosols are inadequately observed and poorly represented in climate models, contributing to the current large uncertainty associated with aerosol–cloud interactions. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) aircraft field campaign near the Azores islands provided ample observations of vertical distributions of aerosol and cloud properties. Here we utilize the in situ aircraft measurements from the ACE-ENA and ground-based remote-sensing data along with an aerosol-aware Weather Research and Forecast (WRF) model to characterize the aerosols due to long-range transport over a remote region and to assess their possible influence on marine-boundary-layer (MBL) clouds. The vertical profiles of aerosol and cloud properties measured via aircraft during the ACE-ENA campaign provide detailed information revealing the physical contact between transported aerosols and MBL clouds. The European Centre for Medium-Range Weather Forecasts Copernicus Atmosphere Monitoring Service (ECMWF-CAMS) aerosol reanalysis data can reproduce the key features of aerosol vertical profiles in the remote region. The cloud-resolving WRF sensitivity experiments with distinctive aerosol profiles suggest that the transported aerosols and MBL cloud interactions (ACIs) require not only aerosol plumes to get close to the marine-boundary-layer top but also large cloud top height variations. Based on those criteria, the observations show that the occurrence of ACIs involving the transport of aerosol over the eastern North Atlantic (ENA) is about 62 % in summer. For the case with noticeable long-range-transport aerosol effects on MBL clouds, the susceptibilities of droplet effective radius and liquid water content are − 0.11 and + 0.14, respectively. When varying by a similar magnitude, aerosols originating from the boundary layer exert larger microphysical influence on MBL clouds than those entrained from the free troposphere.
Optimization of the step feeding ratio for nitrogen removal by SBR using technique for order preference by similarity to ideal solution (TOPSIS)

The performance of nitrogen (N) removal was investigated by altering the influent step feeding in a sequencing batch reactor (SBR). The optimum condition for influent step feeding was analyzed using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with entropy weight method, considering the C/N ratio range 1.5 to 4.5. The results showed that the SBR with the multi-step-feeding system achieved a high nitrogen removal rate of 92.7% at the three-step influent feeding mode. Nitrogen removal was significantly improved due to the multi-step influent feeding, which provided the required carbon source in the anoxic phase for the removal of nitrate that enhanced the denitrification process. The highest nitrogen removal rate at real-time operation was observed at the three-step feeding mode with 60% primary feeding, 30% secondary feeding, and 10% tertiary feeding, respectively. TOPSIS analysis results also showed that the optimum step feeding ratio was identical to the real-time operation of the SBR.
Rental legislation and the changing Icelandic rental market

Rental markets hold an important role for a functioning housing market as a whole. Households with shorter time horizons, as well as households with little private equity and difficulties acquiring capital can see their housing needs met on the rental market. A functioning rental market does however require some sort of legislation. In this paper we argue that legislation must adapt to changing rental markets. We do so from the specific case of Iceland. The Icelandic rental market has, since the financial crisis, undergone noticeable structural change, evident from a number of perspectives. By applying a framework based in the role of rental market legislation, we provide a comparison between legislation in the Nordic countries. We conclude, based both in the presented structural change of the Icelandic rental market, and in aspects of Nordic rent legislation, that there is a case to be made for changes to the Icelandic legislation.