Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent insight into strategies for the design of antimicrobial peptides (AMPs)

With the increasing development of antibiotic resistance among key bacterial pathogens, there is an urgent need to discover novel classes of antibiotics. Although antimicrobial peptides (AMP) with their specific mode of action are considered major candidates for next-generation antibiotics, several challenges limit the use of these peptides for therapeutic applications. In a large body of research, the focus is given to different approaches to the chemical modification of AMPs and how these modifications may improve the stability, antibiotic activity, proteolytic activity and prevent the cytotoxicity and side effects of AMPs. On the other hand, another group of research investigates the delivery of AMPs via nanocarrier systems as strategies used to enhance stability, control the release of peptides and reduce adverse peptide-related side effects, as well as improve their anti-microbial activities. In the present article, we surveyed most recently published researches that provide us with good knowledge on structural features, mechanism of action, therapeutic aim, advantages and limitations, chemical modification approaches and carrying strategies of AMPs. Finally, according to Quality by Design, the most important potential effective factor and potential risk were mentioned in the development of AMP delivery systems.
Review of Mobile Applications Testing with Automated Techniques

As the mobile applications and mobile consumers are rising swiftly, it is concern to researchers and testing professionals to devise viable testing techniques to guarantee unwavering quality of these mobile applications. A proper mobile quality charter would serve developers as a parameter for mobile quality confirmation. Due to smaller development life cycle of mobile applications, the developed apps tend to be faulty as little effort is put in ensuring quality of the app. Thus rigorous testing is required for ensuring its quality and that too in little time. Traditional life cycle models which are used for developing desktop/laptop application, same models are adjusted to work on mobile application development. But because of certain characteristics of mobile applications which are diverse from traditional applications, same models cannot be assimilated for mobile application development. For testing also which is a considered as a phase in mobile application development need to be addressed separately. There is various mobile application testing techniques used such as manual and automated techniques. But much importance is given to automated approach due to its various advantages. This paper discusses the characteristics specific to mobile apps along with comparison of manual and automated testing and comparison of various automated testing techniques precisely used for mobile applications.
Detection of Four Porcine Enteric Coronaviruses Using CRISPR-Cas12a Combined with Multiplex Reverse Transcriptase Loop-Mediated Isothermal Amplification Assay

Porcine enteric coronaviruses have caused immense economic losses to the global pig industry, and pose a potential risk for cross-species transmission. The clinical symptoms of the porcine enteric coronaviruses (CoVs) are similar, making it difficult to distinguish between the specific pathogens by symptoms alone. Here, a multiplex nucleic acid detection platform based on CRISPR/Cas12a and multiplex reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) was developed for the detection of four diarrhea CoVs: porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine deltacoronavirus (PDCoV), and swine acute diarrhea syndrome coronavirus (SADS-CoV). With this strategy, we realized a visual colorimetric readout visible to the naked eye without specialized instrumentation by using a ROX-labeled single-stranded DNA-fluorescence-quenched (ssDNA-FQ) reporter. Our method achieved single-copy sensitivity with no cross-reactivity in the identification and detection of the target viruses. In addition, we successfully detected these four enteric CoVs from RNA of clinical samples. Thus, we established a rapid, sensitive, and on-site multiplex molecular differential diagnosis technology for porcine enteric CoVs.
Diagnostic Classification of Cases of Canine Leishmaniasis Using Machine Learning

Proposal techniques that reduce financial costs in the diagnosis and treatment of animal diseases are welcome. This work uses some machine learning techniques to classify whether or not cases of canine visceral leishmaniasis are present by physical examinations. For validation of the method, four machine learning models were chosen: K-nearest neighbor, Naïve Bayes, support vector machine and logistic regression models. The tests were performed on three hundred and forty dogs, using eighteen characteristics of the animal and the ELISA (enzyme-linked immunosorbent assay) serological test as validation. Logistic regression achieved the best metrics: Accuracy of 75%, sensitivity of 84%, specificity of 67%, a positive likelihood ratio of 2.53 and a negative likelihood ratio of 0.23, showing a positive relationship in the evaluation between the true positives and rejecting the cases of false negatives.
The effect of sampling volume size on the apparent stiffness of jointed rock mass

Overall mechanical properties of a jointed rock mass are strongly affected by discontinuities – fractures – that naturally occur in rocks. Stochastically-generated discrete fracture network (DFN) modeling, which uses a probabilistic approach to describe the spatial distribution of fractures, such as position, size, or orientation, offers an explicit way to describe geometry of the fracture system. Many in-situ measurements and analyses presented in literature indicate that fractures’ sizes can be adequately represented by the power law probability distribution. The parallel plate model of individual fractures combined with an averaging technique makes it possible to estimate the overall compliance or stiffness of jointed rock mass (Oda et al. [1]). In the present study, a series of numerical simulations of jointed rock mass modeled by DFN and Oda’s approach were conducted to analyze the effect of different sizes of the sampling volume on the overall elastic moduli. The results of the numerical study show that the variance as well as the average of the apparent stiffness decrease as the size of sampling element grows.
Exploiting Marketing Methods for Increasing Participation and Engagement in Sustainable Mobility Planning

Experience has shown that when a target group that benefits from or is affected by an intervention is included in the planning procedure from the beginning, underlying success factors are revealed and respected. Coming to sustainable mobility planning, an ideal participatory scheme (optimal synthesis of different perspectives) accompanying the sustainable mobility planning cycle would add to the interventions’ success. The current paper, based on the knowledge acquired within the e-smartec Interreg EUROPE project, is inspired by the wide spectrum of marketing techniques from the business sector and proposes the effective transfer of them to mobility co-planning and citizens’ engagement. The approach for developing this capacity-building guide (MOBENGAGE-RADAR) on engagement in mobility planning includes (i) review of existing appealing marketing techniques (1st level), (ii) extraction of the affiliated engagement methods (2nd level), (iii) identification of real-world examples of successful citizens’ engagement practices (3rd level), and (iv) correlation of methods and examples with SUMP steps. MOBENGAGE-RADAR visualizes the applicability of the different engagement and awareness raising methods for each step of mobility planning and can be used as the base for creative thinking while developing an engagement strategy.
Microstructures and Soft Magnetic Properties of Fe73.5−xCu1Nb3Si13.5B9Gdx (x = 0–1.5) Alloys

In this experiment, the rare earth Gd element was added to Finemet alloy to observe the microstructure and soft magnetic properties. The experimental results showed that the samples with the addition of 0.5% Gd and 1.0% Gd can be quenched and cast normally, and the MS of Fe73Cu1Nb3Si13.5B9Gd0.5 alloy was 10.41% higher than that of Finemet. After annealing, crystal grains of about 10 nm were formed. The μi and μm values of Fe73Cu1Nb3Si13.5B9Gd0.5 alloy were 25.51% and 22.23% higher, respectively, and the coercivity HC was reduced by 12.19% compared to Finemet. At 1 kHz, the μe value of Fe73Cu1Nb3Si13.5B9Gd0.5 alloy at room temperature was 14.57% higher than that of Finemet, while the μe reached 162.34 k and 142.42 k at 90 °C and 150 °C (24% and 29.51% higher, respectively). The Fe72.5Cu1Nb3Si13. 5B9Gd1.0 alloy had the best performance at 100 kHz, with higher μe values than Finemet across the ambient temperature range of 30 °C to 150 °C. After tension annealing, the μe values of Fe72.5Cu1Nb3Si13. 5B9Gd1.0 alloy were 20–30% higher than those of Finemet.
User Experience Evaluation of Student Academic Information System of Higher Education Using User Experience Questionnaire

User experience describes the experience gained by users when using software products. Focus on the needs and emotions of users when using a product is one of the keys to the success of a software. As a software product, Student Academic Information Systems have an important role to improve services to students in Higher Education. Measurement of user experience aims to determine the experience gained by users when using the Student Academic Information System. Measurements were made using the User Experience Questionnaire (UEQ) on 179 active student of a higher education institution in Pekanbaru. The results obtained for each aspect of UEQ are 1.395 attractiveness, 1.586 clarity, 1.380 efficiency, 1.392 accuracy, 1,347 stimulation and 0.847 novelty. The lowest value is in the novelty aspect. The novelty aspect needs to be a concern because users feel the monotonous and usual novelty so that it has a negative impression value. The results of this study can be used as recommendations for designing a new Student Academic Information System user experience.
Deciphering the Assembly of Enveloped Viruses Using Model Lipid Membranes

The cell plasma membrane is mainly composed of phospholipids, cholesterol and embedded proteins, presenting a complex interface with the environment. It maintains a barrier to control matter fluxes between the cell cytosol and its outer environment. Enveloped viruses are also surrounded by a lipidic membrane derived from the host-cell membrane and acquired while exiting the host cell during the assembly and budding steps of their viral cycle. Thus, model membranes composed of selected lipid mixtures mimicking plasma membrane properties are the tools of choice and were used to decipher the first step in the assembly of enveloped viruses. Amongst these viruses, we choose to report the three most frequently studied viruses responsible for lethal human diseases, i.e., Human Immunodeficiency Type 1 (HIV-1), Influenza A Virus (IAV) and Ebola Virus (EBOV), which assemble at the host-cell plasma membrane. Here, we review how model membranes such as Langmuir monolayers, bicelles, large and small unilamellar vesicles (LUVs and SUVs), supported lipid bilayers (SLBs), tethered-bilayer lipid membranes (tBLM) and giant unilamellar vesicles (GUVs) contribute to the understanding of viral assembly mechanisms and dynamics using biophysical approaches.
Population connectivity of aquatic insects in a dam‐regulated, desert river

Humans have exaggerated natural habitat fragmentation, negatively impacting species dispersal and reducing population connectivity. Habitat fragmentation can be especially detrimental in freshwater populations, whose dispersal is already constrained by the river network structure. Aquatic insects, for instance, are generally limited to two primary modes of dispersal: downstream drift in the aquatic juvenile life stages and flight during the terrestrial winged adult stage. Yet the impacts of large hydropower dams can make rivers uninhabitable for incoming (drifting) juvenile insects, with remaining refugia found only in tributaries. The ability of adult aquatic insects to traverse such river stretches in search of suitable tributary habitat likely depends on factors such as species‐specific dispersal ability and distance between tributaries. To explore the intersection of natural and human‐induced habitat fragmentation on aquatic insect dispersal ability, we quantified population genetics of three taxa with varying dispersal abilities, a caddisfly (Hydropsychidae, Hydropsyche oslari), a mayfly (Baetidae: Fallceon quilleri), and a water strider (Veliidae: Rhagovelia distincta), throughout tributaries of the Colorado River in the Grand Canyon, Arizona, USA. Using 2bRAD reduced genome sequencing and landscape genetics analyses, we revealed a strong pattern of isolation by distance among mayfly populations. This contrasts with caddisfly and water strider populations, which were largely panmictic. Analysis of thousands of informative single nucleotide polymorphisms showed that realized dispersal ability may not be accurately predicted by species traits for these widespread species. Principal components analysis revealed a strong division between caddisfly populations upstream and downstream of Havasu Creek (279 km through the 390 km study reach), suggesting that the geography of the Grand Canyon imposes a dispersal barrier for this species. Our use of genetic tools in the Grand Canyon to understand population structure has enabled us to elucidate dispersal barriers for aquatic insects. Ultimately, these data may be useful in informing effective conservation management plans for understudied organisms of conservation interest.
Facial conformation modeling via interactive adjustment of hierarchical linear anthropometry-based parameters

ABSTRACTThis paper presents a new and easy-to-use interactive facial conformation modeling method. The modeling of a specific face is performed on a generic, triangle mesh based face model by adjusting a set of hierarchically organized facial confirmation parameters, which are derived from the anthropometric data on human faces. The method transforms complex facial conformation mesh manipulations into simple linear parameter adjustments between the specified anthropometric landmark points on the face mesh. The parameter adjustments are made interactively via a three-level hierarchical framework. Geodesic distance based compactly supported radial basis functions are employed to smoothly interpolate the displacements of the face mesh vertices and facilitate localized deformation and hole handling on the face mesh. The involved linear anthropometry-based parameters are classified into three different levels with each level governed by its own radial basis functions. Simple and interactive mesh manipulations .
Regional reindustrialization patterns and productivity growth in Europe

ABSTRACT After a long period of deindustrialization, Europe faces ‘the need to reverse the declining role of industry’, as the European Union officially claims, to relaunch productivity. Despite this strong political claim, scientifically sound analyses on whether a reindustrialization process takes place, and if it is accompanied by a relaunch of productivity, are still missing. Drawing on the path-dependence theoretical framework, different reindustrialization patterns are conceptually identified and operationally associated with European NUTS-2 regions thanks to an original database of value added at (sub-manufacturing) sectoral regional level in different time spans. Results suggest that the patterns are associated with different degrees of industry productivity growth. Ad-hoc policies accompanying different reindustrialization modes are suggested. They can help to achieve a critical mass of reindustrialization that could potentially stimulate a still missing effect on aggregate productivity increase.
Characterization of fractional viscoelastic relaxation behavior of a photopolymer film

Photoresponsive polymers are commonly used for applications such as controlled drug delivery, patterned thin films of hydrogels and polymer brushes, photodegradable materials, and liquid crystal actuators.1 Photoresponsive polymers are unique as they can change shape when exposed to a certain wavelength, intensity, or polarization of light while not requiring an electrical circuit or tethered power supply. However, the majority of photoresponsive polymers are based on the azobenzene moiety and the conversion of light into mechanical work is often inefficient. This work summarizes the relaxation behavior of a novel photopolymer film derived from stilbene and its unsensitized analog. Experiments are conducted quantifying the relaxation behavior of the films. The relaxation behavior of the photopolymer is analyzed by comparing fractional order and integer order Maxwell models. All results are statistically validated using Bayesian uncertainty methods to obtain posterior densities for the model parameters. It is shown that the fractional order Maxwell model is superior based on errors that are an order of magnitude lower than the integer order Maxwell model.
Impedance modeling of electromagnetic energy harvesting system using full-wave bridge rectifier

In the conventional model of general vibration energy harvesters, the harvesting effect was regarded as only the electrically induced damping. Such intuition has overlooked the detailed dynamic contribution of practical power conditioning circuits. This paper presents an improved impedance model for the electromagnetic energy harvesting (EMEH) system considering the detailed dynamic components, which are introduced by the most extensively used full-wave bridge rectifier. The operation of the power electronics is studied under harmonic excitation. The waveforms, energy cycles, and impedance picture are illustrated for showing more information about the EMEH system. The theoretical prediction on harvesting power can properly describe the changing trend of the experimental result.
Sekolah Lapang Petani sebagai Community of Practice Pengembangan Inovasi Kelompok di Era Digital

Farmer Field School (FFS) is a learning exchange method used by the farmers to find solution. In this digital era, farmers also exchange knowledge and information through digital platform. The research objective is to investigate the practices of FFS by farmers/female farmers in the form of Community of Practice nowadays. The research was conducted in Situgede Village, Bogor that has a typical of rural-urban community. Data on FFS, business groups and agricultural innovations were collected through in-depth interviews, observations and focus group discussions. The data and information were processed using NVivo software. The results show that the farmers practice FFS to solve on-farm issues, learning methods, cooperation and achieve the group’s objectives. The community groups used social media to communicate in addition to in person’s meetings. Situgede ecotourism development opens job opportunity and new business. The Dalima Female Farmer Group has produced organic red and black rice that sold through direct selling and via an e-commerce up to the end of 2021. One group run by youths produces herbal drink products. All groups have obstacles of water and land availability for agriculture, member participation, and innovation. The groups learn from other villages to solve the issues. In conclusion, FFS as a CoP is practiced based on the current issues faced in the fields.
Visualisation Ability of Senior High School Students with Using GeoGebra and Transparent Mica

Visualisation ability is an ability to process, inform, and transform object which suitable for geometry topic in math. This research aims to describe the influence of using software GeoGebra and transparent mica for student’s visualisation ability. GeoGebra is shortness of geometry and algebra. GeoGebra is an open source program that is created for math. Transparent mica is a tool that is created by the author to transform a geometry object. This research is a quantitative experiment model. The subject of this research were students in grade XII of science program in Annajah Senior High School Rumpin with two classes which one as an experiment class (science one) and another one as a control class (science two). Experiment class use GeoGebra and transparent mica in the study, and control class use powerpoint in the study. Data of student’s visualisation ability is collected from posttest with visual questions which are gifted at the end of the research to both classes with topic “transformation geometry”. This research resulted that studying with GeoGebra and transparent mica had a better influence than studying with powerpoint to student’s visualisation ability. The time of study in class and the habit of the students to use software and tool affected the result of research. Although, GeoGebra and transparent mica can give help to students in transformation geometry topic.
A P&O Based Variable Step Size MPPT Algorithm for Photovoltaic Applications

Highlights • This paper focuses on maximum power point tracking problem. • A modified P&O method is proposed for fast tracking and less oscillations around MPP point. • Results obtained by simulations are verified by an experimental setup. Abstract Maximum power point tracking (MPPT) is an indispensable component of the Photovoltaic (PV) systems to maximize efficiency. Perturb and observe (P&O) is one of the prevalent MPPT methods owing to its easier structure for implementation but it suffers from problems of slow tracking and oscillations around the MPP. In this paper, a modified variable step size MPPT algorithm based on P&O method is proposed to obtain maximum power output from the PV system coupled with a boost DC-DC converter. The proposed method employs the scaled power difference as a control variable to enable variation of step size for each cycle. Results obtained by simulation and experimental work verified that the proposed algorithm is potent mitigating the problems related with classical P&O method.
Path optimization for uniform removal pre-polishing of optical glass with industrial robots

Abstract. In the field of precision optical manufacturing, the manufacturing method using industrial robots as the carrier has highlighted its advantages of being more economical and efficient than existing methods. The application of different end-effectors has expanded the scenarios and processing limits of optical polishing. However, concise and simplified polishing technologies remain challenging. To improve the versatility of industrial robots in different processes and reduce the number of polishing iterations, pre-polishing with uniform removal is introduced and optimized, providing an excellent basic surface for polishing and finishing. Combined with the performance of an industrial robot, we adopt a swing composite path, to which the motion parameters are adjusted and optimized to minimize the fluctuation of the overall overlap rate (within 5%). The optimal path is based on the uniform B-spline curve characterization, which improves the consistency of the dwelling time and reduces the complexity of pre-polishing, laying a theoretical foundation for efficient and high-quality optical manufacturing.