Miracle-dz/UniFAR-FTUs huggingface dataset:
Mounding technique improves physiological performance and yield of oil palm on Spodosols

Spodosols have been widely used for oil palm plantations, specifically in Kalimantan, Indonesia. However, they are sub-optimal for agriculture due to a lack of water and nutrient-holding capacity and a spodic layer that limits plant root development. Therefore, proper agriculture practices are needed for oil palm to enhance its potential yield. This study aims to determine the effect of the mounding technique on the physiological performance and yield of oil palms in spodosol. The study location was well-managed, with eight blocks of oil palm plantations planted in 2008 on spodosols (Typic Haplohumod) in Central Kalimantan. The mounding technique was applied to four blocks of oil palm planted in 2015, while the remaining four were left without mounding. The parameters observed were soil moisture, transpiration, number of bunches, bunch weight, and yield. The results showed that the average moisture in the mounded soil was 4% greater than the control. Additionally, the average daily transpiration of oil palm with the mounding was up to 2.30 mm day-1 or three times higher than the control. The implication was that the average yield of oil palm increased from approximately 1.84 to 3.71 tons ha-1 year-1 compared to no-mounding treatments. Furthermore, the average yield was 19-66% higher than the block without the mounding application.
CoDe: a web-based tool for codon deoptimization

Abstract Summary We have developed a web-based tool, CoDe (Codon Deoptimization) that deoptimizes genetic sequences based on different codon usage bias, ultimately reducing expression of the corresponding protein. The tool could also deoptimize the sequence for a specific region and/or selected amino acid(s). Moreover, CoDe can highlight sites targeted by restriction enzymes in the wild-type and codon-deoptimized sequences. Importantly, our web-based tool has a user-friendly interface with flexible options to download results. Availability and implementation The web-based tool CoDe is freely available at https://web.iitm. ac.in/bioinfo2/codeop/landing_page. html. Supplementary information Supplementary data are available at Bioinformatics Advances online.
Multimodal Locomotion and Cargo Transportation of Magnetically Actuated Quadruped Soft Microrobots

Untethered microrobots have attracted extensive attention due to their potential for biomedical applications and micromanipulation at the small scale. Soft microrobots are of great research importance because of their highly deformable ability to achieve not only multiple locomotion mechanisms but also minimal invasion to the environment. However, the existing microrobots are still limited in their ability to locomote and cross obstacles in unstructured environments compared to conventional legged robots. Nature provides much inspiration for developing miniature robots. Here, we propose a bionic quadruped soft thin-film microrobot with a nonmagnetic soft body and 4 magnetic flexible legs. The quadruped soft microrobot can achieve multiple controllable locomotion modes in the external magnetic field. The experiment demonstrated the robot’s excellent obstacle-crossing ability by walking on the surface with steps and moving in the bottom of a stomach model with gullies. In particular, by controlling the conical angle of the external conical magnetic field, microbeads gripping, transportation, and release of the microrobot were demonstrated. In the future, the quadruped microrobot with excellent obstacle-crossing and gripping capabilities will be relevant for biomedical applications and micromanipulation.
Machine Learning for Securing Traffic in Computer Networks

—Computer network attacks are among the most significant and common threats against computer-wired and wireless communications. Intrusion detection technology is used to secure computer networks by monitoring network traffic and identifying attacks. In this paper, we investigate and evaluate the application of four machine learning classification algorithms for identifying attacks that target computer networks: DDoS, Brute Force Web, and SQL Injection attacks, in addition to Benign Traffic. A public dataset of 80 features was used to build four machine learning models using Random Forest, Logistic Regression, CN2, and Neural Networks. The constructed models were evaluated based on 10-fold cross-validation using Classification Accuracy (CA), Area under the Curve (AUC), F1, Recall, Specificity, and Sensitivity metrics in addition to Confusion Matrix, Calibration, Lift, and ROC plots. The Random Forest model achieved 98% in the CA score and 99% in the AUC score, while the Logistic regression achieved 90% in the CA score and 98% in the AUC score.
Effects of pressure fluctuations on turbulence growth in compressible homogeneous shear flow

Direct numerical simulation results are used to study compressibility effects on turbulent energy growth in homogeneous shear flow. Normalized amplitude of the pressure fluctuations is shown to decrease as the turbulent Mach number increases. This decrease causes the reduction in the pressure–strain term, changes the anisotropy of the Reynolds stress, and reduces the growth rate of turbulent kinetic energy as is the case of mixing layers. The transport equation for the pressure variance is examined in detail. It is shown that when the turbulent Mach number is high the pressure-variance dissipation term is not negligible and contributes to the reduction in the pressure fluctuations. The pressure-variance dissipation is closely related to the high-wavenumber part of the pressure-variance spectrum. Profile of the spectrum is observed to depend on the turbulent Mach number. A statistical theory called the two-scale direct-interaction approximation is applied to obtain model expressions for pressure-related te.
Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments

Aluminium is extensively used in many manufacturing processes because of its intrinsic properties like soft, ductile, high electrical conductivity and highly corrosion resistant. Unfortunately, pure aluminium cannot give a required tensile strength, whereas by adding some other materials like particles of silicon carbide can give a proper strength and converted into a composite with adequate properties which is most suitable in the manufacturing of some specific biomedical instruments. It is well known that size and spatial distributions of particles are both influential in determining the mechanical properties of composite materials and, therefore, statistical characterization of these distributions is of prime importance if we wish to control the quality of the manufacturing processes for these materials. Many researchers have considered quantitative analysis of these features separately, but here we investigate the relationship between size and spatial distribution of the particles over an aluminium matrix. We have considered the actual sizes simply as ‘large’ or ‘small’ and, consequently, the characterization of the particle distribution patterns in the aluminium matrix can be carried out using statistical methods based on the theory of bivariate spatial point processes. We have applied this statistical approach to a sample of an aluminium alloy reinforced with silicon carbide particles. It is shown that the methods provide a complete characterization on the spatial interaction between small and large silicon carbide particles and it can be successfully used in a quality control step for the production of particulate composite materials used in the manufacturing of biomedical instruments.
Sequência didática

Essa sequência didática traz a problematização da alimentação saudável e qualidade de vida para a sala de aula com questionamentos que aguçam o aluno a refletir e repensar sobre os seus hábitos alimentares, uma vez que são estimulados a analisar e interpretar informações contidas nas embalagens dos alimentos. Constitui uma proposta metodológica pautada no protagonismo discente com métodos que otimizam a autonomia do aluno através de um viés investigativo, com base na pesquisa, problematização, diálogo, observação, análise crítica, confronto de ideias, reflexão e avaliação dos dados. Dispõe de recursos práticos e de fácil acesso, com estratégias que contribuem para um ensino e aprendizagem mais dinâmico, atraente, contextualizado e significativo. Tendo como objetivo principal instigar a curiosidade do aluno para a leitura e interpretação de rótulos alimentares, em busca de uma alimentação saudável e equilibrada.
Hybrid Deep Learning Architecture for Land Use - Land Cover Images Classification with a Comparative and Experiemental Study

—Deep Learning algorithms have become more popular in computer vision, especially in the image classification field. This last has many applications such as moving object detection, cancer detection, and the classification of satellite images, also called images of land use-land cover (LULC), which are the scope of this paper. It represents the most commonly used method for decision making in the sustainable management of natural resources at various geographical levels. However, methods of satellite images analysis are expensive in the computational time and did not show good performance. Therefore, this paper, on the one hand, proposes a new CNN architecture called Modified MobileNet V1 (MMN) based on the fusion of MobileNet V1 and ResNet50. On the other hand, it presents a comparative study of the proposed model and the most used models based on transfer learning, i.e. MobileNet V1, VGG16, DenseNet201, and ResNet50. The experiments were conducted on the dataset Eurosat, and they show that ResNet50 results emulate the other models.
Nicotinonitrile as an essential scaffold in medicinal chemistry: an updated review (2015– present)

Many studies have been carried out to find synthetic pathways to nicotinonitriles (3-cyanopyridines) and their analogs, which has resulted in a substantial amount of knowledge on their biological, therapeutic, and medical characteristics. Some of nicotinonitrile derivatives have emerged as marketed drugs such as bosutinib, milrinone, neratinib
Determinants of tax attitude in small and medium enterprises: Evidence from Indonesia

Abstract This study investigates the extent to which tax literacy, power, and trust strengthen tax attitudes in Indonesian micro, small, and medium enterprises. To meet this objective, this study analyzes (1) the effect of tax literacy on trust and power, (2) the effect of trust and power on voluntary compliance and tax avoidance, and (3) the direct and indirect effects of tax literacy on voluntary compliance and tax avoidance through trust and authority. The findings indicate that tax literacy is very important in determining trust and power. Further, trust and tax authority are important to create a synergistic climate that encourages increased voluntary compliance. Despite evidence that trust in tax authorities is likely to reduce tax evasion, the power of tax authorities had no significance in determining tax evasion. In this case, power was present solely because of the tax obligations imposed through tax regulations rather than legitimacy. Additionally, this study found that trust in authority and the power of authority mediate the relationship between tax literacy and voluntary compliance. Hence, it demonstrates that voluntary compliance depends on whether or not trust and power create legitimacy in the view of taxpayers. A stronger perception of trust and power can ultimately increase tax compliance. For SMEs, the role of tax literacy is crucial, as it helps SMEs understand the facilities provided by the government in the form of tax privileges or facilities. This research uncovered the importance of tax knowledge and its benefits for SMEs in terms of understanding their situation regarding tax. Further, SMEs would be better placed to understand the privileges provided by the government if tax administration principles were simplified.
Robust H-infinity filtering in finite frequency domain for polytopic systems with application to in-band quantisation noise reduction in uncertain cascaded sigma-delta modulators

This study investigates the problem of robust H ∞ filtering in finite frequency domain for polytopic systems. Robust fixed-order, infinite-impulse-response (IIR) and finite-impulse-response (FIR) designs via indirect approach and direct method are presented. The aforementioned techniques refer to the conventional loop shaping method and that uses recently introduced generalised Kalman-Yakubovich-Popov (GKYP) lemma, respectively. The authors consider a frequency-domain polytopic model which includes two well-known special cases, that is, the interval plants and the set of transfer functions with affinely dependent uncertain parameters belonging to a convex-bounded polyhedral domain. They derive conditions for the existence of linear-time invariant (LTI) filters. These conditions, irrespective of the uncertain parameters, guarantee both asymptotic stability of the polytopic systems and the filters, and a guaranteed H ∞ performance in finite frequency domain. Extension of the results to the multi-band case is straightforward, where the advantages of arbitrary filter order and dropping the use of weighting functions is even more obvious. As an example, the authors apply the proposed methods to in-band quantisation noise reduction for uncertain cascaded sigma-delta modulators. By comprehensive comparisons with existing methods, they show the viability and efficiency of their design.
Directivity of acoustic emissions from wave packets to the far field

We investigate the acoustic emission from wave packets to the far field. To this end, we develop a theory for one- and two-dimensional source fields in the shape of wave packets with Gaussian envelopes. This theory is based on an approximation to Lighthill's acoustic analogy for distant observers. It is formulated in the spectral domain in which a Gaussian wave packet is represented again by a Gaussian. This allows us to determine the directivity of the acoustic emission (e.g. superdirectivity and Mach waves) by simple geometric constructions in the spectral domain. It is shown that the character of the acoustic emission is mainly governed by the aspect ratio and the Mach number of the wave packet source. To illustrate the relevance of this theory we use it to study two prominent problems in subsonic jet aeroacoustics.
The formalization of fairness: issues in testing for measurement invariance using subtest scores

Measurement invariance is an important prerequisite for the adequate comparison of group differences in test scores. In psychology, measurement invariance is typically investigated by means of linear factor analyses of subtest scores. These subtest scores typically result from summing the item scores. In this paper, we discuss 4 possible problems related to this common practice. Specifically, we discuss (a) nonlinearity of the latent variable to subtest relation; (b) suboptimality of the total score as a proxy for the latent variable measured through the item scores; (c) non-normality of the subtest score; and (d) differences in the nature of the latent variable at the item level as compared to the latent variable at the subtest level. Additionally, we give guidelines to overcome these problems and illustrate the issues by analysing data that pertain to a performal IQ data set.
A Theoretical Model of Using Extended Reality in Architecture Design Education

: Architecture design education is looking for new ways to become more efficient and adaptable to the needs of society. Intensive research is being conducted all over the world to determine how technology, specifically Extended Reality (XR), can be used in design education. The concept of Extended Reality is one of the newest developments that has gained popularity. This paper presents a theoretical model for integrating the basic concepts of XR, especially Virtual Reality (VR) and Augmented Reality (AR), with the architecture design process through the process-based studio teaching stages and the conditions of the design activity, whether it is happening in the design studio crits session or in individual design sessions. The theoretical model is developed through the examination of the architecture design process, the benefits, and previous attempts of using XR in design education. The paper presents the model key concepts, elements and potential applications and points out towards future direction of research.
Determinants of sexual function in men living with HIV younger than 50 years old: Focus on organic, relational, and psychological issues

Sexual dysfunctions, particularly erectile dysfunction, are common in men living with HIV, whose organic and psychological components remain to be clarified. The aim of the study is to investigate the impact of risk factors of sexual dysfunctions, including organic, relational, and psychological determinants of erectile function, in men living with HIV younger than 50 years old.
Classical and quantum ABCD-transformations and the propagation of coherent and Gaussian beams

We develop the mathematical properties of the ABCD-transformation from the classical and quantum mechanical points of view. First, we list the four types of generating function which generate the ABCD-transformation in classical mechanics. Second, we introduce the unitary operator of the ABCD-transformation. Next, we calculate the normal ordering of this unitary operator and derive the kernels in coordinate-momentum phase space. The kernels are comprised of the generating functions, which generate the ABCD-transformation in classical mechanics. This reveals a new correspondence between classical and quantum mechanics. As an application of these kernels, we show the propagation of coherent and Gaussian beams in the context of quantum optics which corresponds to the ABCD-transformation in matrix optics.
hronic nitrogen deposition and the composition of active arbuscular ycorrhizal fungi

A growing body of evidence indicates that atmospheric nitrogen (N) deposition can alter the composition and function of arbuscular mycorrhizal fungi (AMF) associated with plant roots. We studied the community of AMF actively transcribing ribosomal genes in the forest floor of northern hardwood forests dominated by sugar maple (Acer saccharum Marsh.) that have been exposed to experimental N deposition since 1994 (30 kg NO3−-N ha−1 year−1). Our objective was to evaluate whether previously observed declines in AM root infection and mycelial production resulted in a compositional shift in the AM fungi actively providing resources to plant symbionts under chronic N deposition. To accomplish this task, we
On fully nonlinear, vertically trapped wave packets in a stratified fluid on the f-plane

The ubiquity of solitary and solitarylike internal waves in the coastal ocean has been recognized for some time. Recent theoretical studies of a strongly nonlinear, weakly nonhydrostatic set of layer-averaged model equations have predicted that rotation, for example, on the f-plane, can lead to the decay and subsequent reemergence of internal solitary waves. We reconsider this problem using high resolution numerical simulations of the rotating stratified Euler equations. We find that in certain cases the initial disturbances indeed fission into nonlinear wave packets, with the constituent waves making up the wave packet being, in themselves, nonlinear. However, for typical coastal ocean parameters this only occurs at rotation rates higher than those on Earth on the time scales we are able to simulate. We confirm, using the Dubreil–Jacotin–Long equation, that the vertical structure of the wave-induced currents is well predicted by the fully nonlinear theory of nonrotating internal solitary waves and that w.
Fe:ZnSe passive Q-switching of 2.8-&mgr;m Er:Cr:YSGG laser cavity

The use of Fe:ZnSe polycrystals as passive Q-switches for the Er:Cr:YSGG laser operating at 2.8&mgr;m is introduced. Fe:ZnSe samples with 1-7cm-1 coefficients of absorption were prepared using thermal diffusion of iron in CVD grown polycrystalline ZnSe. A flashlamp pumped Er:Cr:YSGG laser with a variable (40 - 80% reflectivity) output coupler (OC) was used as a test bed for passive Q-switching. Using a 90% initial transmission Fe:ZnSe placed at the Brewster angle we obtained a single giant pulse lasing with a pulse duration of ~65 ns and a maximum output of 13 mJ under 30 J of flashlamp pump. Multi-pulse (19 pulses) output was obtained with 85 mJ total output energy at a pump energy of 30 J. The saturation curve of Fe:ZnSe was measured. Fitting this data with a theoretical model results in absorption crosssection of 0.56 × 10-18 cm2, which is close to the value of the absorption cross-section obtained from spectroscopic measurements (0.85 × 10-18 cm2 at 2.8 &mgr;m).
Hybrid Modeling to Classify and Detect Outliers on Multilabel Dataset based on Content and Context

— Due to the linked various matching categories, news article categorization are a rapidly increasing field of interest in text classification. However, the low-reliability indices and ambiguities related to frequently used province classifiers restrict success in this field. Most of the existing research uses traditional machine learning algorithms. It has weaknesses in training large-scale datasets, and data sparseness often occurs from short texts. Therefore, this study proposed a hybrid model consisting of two models, namely the news article classification and the outlier detection model. The news article classification model used a combination of two deep learning algorithms (Long Short-Term Memory dan Convolutional Neural Network) and outlier classifier model, which was intended to predict the outlier news using a decision tree algorithm. The proposed model's performance was compared against two widely used datasets. The experimental results provide useful insights that open the way for a number of future initiatives.
Two‐Photon Polymerization: Fundamentals, Materials, and Chemical Modification Strategies

Two‐photon polymerization (TPP) has become a premier state‐of‐the‐art method for microscale fabrication of bespoke polymeric devices and surfaces. With applications ranging from the production of optical, drug delivery, tissue engineering, and microfluidic devices, TPP has grown immensely in the past two decades. Significantly, the field has expanded from standard acrylate‐ and epoxy‐based photoresists to custom formulated monomers designed to change the hydrophilicity, surface chemistry, mechanical properties, and more of the resulting structures. This review explains the essentials of TPP, from its initial conception through to standard operating principles and advanced chemical modification strategies for TPP materials. At the outset, the fundamental chemistries of radical and cationic polymerization are described, along with strategies used to tailor mechanical and functional properties. This review then describes TPP systems and introduces an array of commonly used photoresists including hard polyacrylic resins, soft hydrogel acrylic esters, epoxides, and organic/inorganic hybrid materials. Specific examples of each class—including chemically modified photoresists—are described to inform the understanding of their applications to the fields of tissue‐engineering scaffolds, micromedical, optical, and drug delivery devices.