Traditional Research Articles

Traditional Phytotherapy amongst the Rural Communities of North Western Himalaya

This paper deals with 73 species of medicinal plants used by the traditional communities of Kullu district of north western Himalaya, forest wealth and traditional wisdom. An attempt has been made to record interesting folk-uses and medicinal plant lore used by the people at Chhakinal watershed in Kullu district of north western Himalaya.

Traditional Herbal Remedies among the Bhilalas of West Nimar District, M.P, India

Traditional herbal remedies common among the Bhilalas of West Nimar district of Madhya Pradesh are reported. In all 29 species belonging to 28 genera and 21 families are recorded. Their correct scientific names, local names, parts used and mode of administration are mentioned for each plant.

Ethno-Medicobotanical Survey in Dharwad-Plants Used for Jaundice

Dharwad district is situated at an elevation of 678 m. above MSL. This district is adjacent to Western Ghats. There are several herbal practitioners who depend mostly on the locally available plants. There is no published data on the ethno-medico botanical study of this district and hence an extensive survey was undertaken between 1999-2001. More than 200 traditional herbal practitioners were contacted, amongst whom 54 are effectively treating the jaundice. Twenty five species belonging to 18 families used for curing jaundice in Dharwad district of Karnataka have been recorded. Amongst these species, the most commonly used are Eclipta prostrata L., Plumbago zeylanica L., Ricinus communis L., Balanites aegyptlaca (L) Delile., Phyllanthus niruri L . and Tinospora cordifolia Miers. The method of preparation of medicines disclosed by few of the practitioners are discussed.

Time-first approach for land cover mapping using big Earth observation data time-series in a data cube – a case study from the Lake Geneva region (Switzerland)

ABSTRACT Accurate, consistent, and high-resolution Land Use & Cover (LUC) information is fundamental for effectively monitoring landscape dynamics and better apprehending drivers, pressures, state, and impacts on land systems. Nevertheless, the availability of such national products with high thematic accuracy is still limited and consequently researchers and policymakers are constrained to work with data that do not necessarily reflect on-the-ground realities impending to correctly capture details of landscape features as well as limiting the identification and quantification of drivers and rate of change. Hereafter, we took advantage of the Switzerland’s official LUC statistical sampling survey and dense time-series of Sentinel-2 data, combining them with Machine and Deep Learning methods to produce an accurate and high spatial resolution land cover map over the Lake Geneva region. Findings suggest that time-first approach is a valuable alternative to space-first approaches, accounting for the intra-annual variability of classes, hence improving classification performances. Results demonstrate that Deep Learning methods outperform more traditional Machine Learning ones such as Random Forest, providing more accurate predictions with lower uncertainty. The produced land cover map has a high accuracy, an improved spatial resolution, while at the same time preserving the statistical significance (i.e. class proportion) of the official national dataset. This work paves the way towards the objective to produce a yearly high resolution land cover map of Switzerland and potentially implement a continuous land change monitoring capability. However further work is required to properly address challenges such as the need for increased temporal resolution for LUC information or the quality of training samples.

Information technologies in the management of technological processes for the production of building products

The object of the study is the production of construction products with fillers from recycled wind turbine blades. The study solves the problem related to the possibility of using fillers from recycled wind turbine blades in the technological process of manufacturing construction products. According to the results of the study, concrete mixtures with the most optimal formulations that meet the requirements of state standards were classified, this was achieved due to effective indicators reflecting the characteristics of concrete mixtures. The developed algorithm of the technological process of production of building products was used in the development of the program code, this became possible due to the consideration of assumptions and limitations of the technological equipment used in production. The program for managing the technological process of manufacturing construction products is developed in C++, which does not require additional resources for auxiliary operations, has the ability to metaprogram and has the necessary performance. The adequacy of the model is ensured by the maximum approximation to real production. The effectiveness of research results in real production is explained by high-quality mixtures, dosage of ingredients, optimal parameters of technological equipment, process control based on data obtained by modeling, which reduces the number of defects and increases equipment productivity. The conditions for using the results of the study are the legislation of the country related to environmental requirements, as well as compliance with the technological process. For the resulting construction products, the bending strength increased by 20 % compared to traditional ones, the number of defects does not exceed 15 %, and equipment productivity increased by 12 %

Four port MIMO antenna for IoT applications in public safety band and sub-6 GHz TDD 5G band

This paper proposes a Multi Input Multi Output (MIMO) antenna specifically developed for Internet of Things (IoT) Applications in Public Safety 4.9 GHz (4940–4990 MHz) band and Sub-6 GHz TDD 5G band (4800–4990 MHz). The proposed MIMO antenna consists of Koch fractal element, and it is introduced in four port configuration. HFSS is used to design, analyze, and optimize the performance parameters of the introduced MIMO antenna. To achieve optimum performance in terms of isolation, initially all two radiating elements of 1 × 2 MIMO configuration with varying orientations have been evaluated, which are positioned on top of a cost-effective FR4 substrate. Later on 2 × 2 and 1 × 4 MIMO configurations are evaluated; and 1 × 4 configuration is fabricated and tested in lab for the verification of simulated results. The MIMO antenna demonstrates resonance at 4.97 GHz, offering a bandwidth of 320 MHz (4795–5115 MHz). It exhibits excellent performance with Envelope Correlation Coefficient (EC-C) < 0.4, Diversity Gain (D-G) > 9.8, Mean Effective Gain (ME-G) < 3 dB, Total Active Refection Coefficient (TAR-C) < −14 dB, Channel Capacity Loss (CC-L) < 0.4 bits/s/Hz, and Isolation < −20 dB across the entire operating frequency range. The proposed MIMO antenna has a maximum gain of 1.2 dBi and radiation efficiency (η) of 80%. This proposed antenna offers several advantages over traditional ones, including high efficiency (η), low CC-L, and significant isolation, even without the use of special techniques to achieve isolation.

Promoting 21st century pedagogy: can school autonomy and school-based professional development processes make a difference?

ABSTRACT Public schools are expected to ensure that students who graduate the kindergarten (for 5–6 year olds) through twelfth grade (for 17–18 year olds) system are adept in 21st century skills to be successful in the new workforce landscape. Hence, schools need to establish progressive teaching and learning processes that significantly differ from the traditional ones. Since learning environments designed for knowledge construction promote self-regulated and self-directed learners, the current study attempts to assess to what extent do teachers’ perceptions of their school’s autonomy and satisfaction with school-based professional development (PD) processes foster 21st century oriented pedagogy. Data were collected from 645 teachers in 64 Israeli public junior high schools through questionnaires. A positive association was found between teachers’ perceived school autonomy and their satisfaction with school-based PD processes. High teacher satisfaction with PD was positively associated with progressive pedagogy. Teachers’ satisfaction with PD mediated the effect of school autonomy on using technology in teaching, on 21st century pedagogical knowledge, and on teachers’ professional competence. School autonomy with the mediation of teachers’ satisfaction with PD processes makes a positive contribution to teachers’ professional competence, knowledge related to progressive teaching and the use of technology. Theoretical and practical implications are further discussed.

The Optimization of a Natural Language Processing Approach for the Automatic Detection of Alzheimer's Disease Using GPT Embeddings.

The development of noninvasive and cost-effective methods of detecting Alzheimer's disease (AD) is essential for its early prevention and mitigation. We optimize the detection of AD using natural language processing (NLP) of spontaneous speech through the use of audio enhancement techniques and novel transcription methodologies. Specifically, we utilized Boll Spectral Subtraction to improve audio fidelity and created transcriptions using state-of-the-art AI services-locally-based Wav2Vec and Whisper, alongside cloud-based IBM Cloud and Rev AI-evaluating their performance against traditional manual transcription methods. Support Vector Machine (SVM) classifiers were then trained and tested using GPT-based embeddings of transcriptions. Our findings revealed that AI-based transcriptions largely outperformed traditional manual ones, with Wav2Vec (enhanced audio) achieving the best accuracy and F-1 score (0.99 for both metrics) for locally-based systems and Rev AI (standard audio) performing the best for cloud-based systems (0.96 for both metrics). Furthermore, this study revealed the detrimental effects of interviewer speech on model performance in addition to the minimal effect of audio enhancement. Based on our findings, current AI transcription and NLP technologies are highly effective at accurately detecting AD with available data but struggle to classify probable AD and mild cognitive impairment (MCI), a prodromal stage of AD, due to a lack of training data, laying the groundwork for the future implementation of an automatic AD detection system.

Assessing the salinization mechanisms of coastal brackish springs

Brackish springs have been extensively reported in Mediterranean coastal carbonate formations. The phenomenon is puzzling because these springs may discharge high flow rates with significant salinities at elevations of several meters above sea level. Although these springs have been studied for millennia (since the ancient Greeks), controversy persists. In essence, they are typically assumed to consist of a karstic conduit bringing fresh groundwater that meets a saltwater conduit at a branching point, where the brackish mixture flows up to the spring mouth. Here, we analyze the hydraulics of the system for two simple cases, depending on whether seawater flow occurs through an open conduit or a porous aquifer. To this end, we derive the equations governing variable-density turbulent flow through the conduits. These turn out to be similar to the traditional ones, except that (1) Bernouilli’s head (energy per unit weight) is substituted by the energy per unit volume, and (2) this energy is not a potential, as a flow path dependent term needs to be added. We solve these equations to obtain the characteristic functions relating fresh to seawater discharge depending on spring concentration. These functions are specific to every brackish spring and representative of the karst system and salinization mechanism. They allow us to show that the spring salinity is mostly controlled by the weight of the water column flowing towards the spring mouth (for low flow rates) and by energy dissipation (for high flow rates). When concentration and flow rate data are available, it is possible to characterize: (1) the resistance of the upwards conduit from the response at high flow rate; (2) the depth of the branching point from the concentration at low discharges; and (3) the hydraulic resistance of the seawater conduit from the slope of concentration vs. flow rate at low spring discharges. These patterns are compared to field data from three different springs, which yields insights on the conceptual model governing every particular spring.

Reliability of Domestic Gas Flow Sensors with Hydrogen Admixtures.

Static flow sensors (e.g., thermal gas micro electro-mechanical sensors-MEMS-and ultrasonic time of flight) are becoming the prevailing technology for domestic gas metering and billing since they show advantages in respect to the traditional volumetric ones. However, they are expected to be influenced in-service by changes in gas composition, which in the future could be more frequent due to the spread of hydrogen admixtures in gas networks. In this paper, the authors present the results of an experimental campaign aimed at analyzing the in-service reliability of both static and volumetric gas meters with different hydrogen admixtures. The results show that the accuracy of volumetric and ultrasonic meters is always within the admitted limits for subsequent verification and even within those narrower of the initial verification. On the other hand, the accuracy of the first generation of thermal mass gas flow sensors is within the limits of the verification only when the hydrogen admixture is below 2%vol. At higher hydrogen content, in fact, the absolute weighted mean error ranges between 3.5% (with 5%vol of hydrogen) and 15.8% (with 10%vol of hydrogen).

Comprehensive analysis of bio-inspired laminated composites plates using a quasi-3D theory and higher order FE models

A comprehensive study is carried out by employing various finite element models (FEMs) for the bending, buckling stability and free vibration analyses of bio-inspired helicoidal composite plates with various lamination schemes. A higher order quasi-3D kinematic plate theory is developed to include a shear deformation effect. The variational formulation of the problem is exploited to derive the equations of motion, element stiffness, geometrical stiffness, and mass matrices based on a non-conforming rectangular element. Three different finite elements models are derived based on non-conforming elements with different number of nodes and degree of freedom. The developed finite element model has been validated with those found in the open literature. The effects of boundary condition, lamination scheme, orthotropy ratio and aspect ratio on the mechanical response of the bio-inspired helicoidal composite plates are examined. Notably, for the lamination schemes investigated in this study, no shear locking phenomenon was observed in the analyses conducted using these FEMs. Dimensionless centre deflections, critical buckling loads and fundamental frequencies of bio-inspired helicoidal composite plates vary depending on the type of lamination scheme, boundary condition and aspect ratio. The new orientation schemes can replace the traditional ones to overcome the shear singularity and overcome the delamination defects.

Energy-Constrained Scheduling for Weakly Hard Real-Time Systems Using Standby-Sparing

For real-time embedded systems, QoS (Quality of Service), fault tolerance, and energy budget constraint are among the primary design concerns. In this research, we investigate the problem of energy constrained standby-sparing for both periodic and aperiodic tasks in a weakly hard real-time environment. The standby-sparing systems adopt a primary processor and a spare processor to provide fault tolerance for both permanent and transient faults. For such kind of systems, we firstly propose several novel standby-sparing schemes for the periodic tasks which can ensure the system feasibility under tighter energy budget constraint than the traditional ones. Then based on them integrated approachs for both periodic and aperiodic tasks are proposed to minimize the aperiodic response time whilst achieving better energy and QoS performance under the given energy budget constraint. The evaluation results demonstrated that the proposed techniques significantly outperformed the existing state-of-the-art approaches in terms of feasibility and system performance while ensuring QoS and fault tolerance under the given energy budget constraint.

Convergence of Nanotechnology and Bacteriotherapy for Biomedical Applications.

Bacteria have distinctive properties that make them ideal for biomedical applications. They can self-propel, sense their surroundings, and be externally detected. Using bacteria as medical therapeutic agents or delivery platforms opens new possibilities for advanced diagnosis and therapies. Nano-drug delivery platforms have numerous advantages over traditional ones, such as high loading capacity, controlled drug release, and adaptable functionalities. Combining bacteria and nanotechnologies to create therapeutic agents or delivery platforms has gained increasing attention in recent years and shows promise for improved diagnosis and treatment of diseases. In this review, design principles of integrating nanoparticles with bacteria, bacteria-derived nano-sized vesicles, and their applications and future in advanced diagnosis and therapeutics are summarized.

Rock Sanctuaries of Apollo in Southern Pisidia: Traditional and “Author’s”

Most rock sanctuaries founded in the mountains of Taurus in the 1st – 3rd century AD had a votive character. These sanctuaries belonged to different deities. In southern Pisidia, three traditional rock sanctuaries of Apollo are known: in Perminus, near the city of Pednelissos, and near the ancient city, whose ruins are located near Kocaaliler. The iconography of Apollo in these sanctuaries differs from the image of a naked god familiar to the Greeks. On the votive stelae from Perminus, Apollo is represented as a rider-god, and in two other sanctuaries the image of the god reproduces the basic principles of the idea of the local god of the Pamphylian city of Side, the so-called Apollo Sidetes. But in the 2nd half of the 2nd century AD, a resident of the city of Adada named Leontianos founded near the road in Yazılı kanyon his “author’s” sanctuary. Based on the traditional votive principle, Leontianos carved on the rock his own verses containing hortations in Stoic philosophy and presented his walking stick as a gift to Apollo. This walking stick symbolized the rejection of reliance on everything material and the achievement of inner freedom, which was taught by Epictetus. The author provides a comparative description of these sanctuaries and points out how the idea of erecting an “author’s” sanctuary arose from the tradition of founding votive sanctuaries and how this new sanctuary differed from the traditional ones.

An unrestricted Arnold’s cat map transformation

AbstractThe Arnold’s Cat Map (ACM) is one of the chaotic transformations, which is utilized by numerous scrambling and encryption algorithms in Information Security. Traditionally, the ACM is used in image scrambling whereby repeated application of the ACM matrix, any image can be scrambled. The transformation obtained by the ACM matrix is periodic; therefore, the original image can be reconstructed using the scrambled image whenever the elements of the matrix, hence the key, is known. The transformation matrices in all the chaotic maps employing ACM has limitations on the choice of the free parameters which generally require the area-preserving property of the matrix used in transformation, that is, the determinant of the transformation matrix to be $$\pm 1.$$ ± 1 . This reduces the number of possible set of keys which leads to discovering the ACM matrix in encryption algorithms using the brute-force method. Additionally, the period obtained is small which also causes the faster discovery of the original image by repeated application of the matrix. These two parameters are important in a brute-force attack to find out the original image from a scrambled one. The objective of the present study is to increase the key space of the ACM matrix, hence increase the security of the scrambling process and make a brute-force attack more difficult. It is proved mathematically that area-preserving property of the traditional matrix is not required for the matrix to be used in scrambling process. Removing the restriction enlarges the maximum possible key space and, in many cases, increases the period as well. Additionally, it is supplied experimentally that, in scrambling images, the new ACM matrix is equivalent or better compared to the traditional one with longer periods. Consequently, the encryption techniques with ACM become more robust compared to the traditional ones. The new ACM matrix is compatible with all algorithms that utilized the original matrix. In this novel contribution, we proved that the traditional enforcement of the determinant of the ACM matrix to be one is redundant and can be removed.

Peasant Food Provision Strategies and Scientific Proposals for Famine Foods in Eighteenth-Century Sweden

The peasant diet during the Little Ice Age in Sweden was mainly grain-based (bread, gruel, and porridge), and the country was heavily dependent on grain imports to meet the population’s needs for food. During the eighteenth century in particular, when famines were frequent following failed harvests, Swedish peasants utilized a range of locally available resources to survive. Bark bread made of cambium (phloem) from Pinus sylvestris was, for example, commonly used as famine food. Scientists of the Enlightenment period and the state authorities tried to alleviate hunger and poverty through the introduction of new food resources and cooking techniques, including wild or agricultural plants such as lichens or potato, and the use of protein sources different from the traditional ones, such as horse meat. However, many of these proposals encountered strong resistance from the peasantry, and only at the end of the 1800s famines ceased to cause suffering in Sweden. Scientific studies have so far focused mainly on mortality, malnutrition, demography, and official responses to famines; yet the question of what the starving peasants gathered, prepared, and consumed is important for the understanding of the historical situation. Also, the difference between the scientific proposals and peasants’ decisions and choices must be clearly distinguished. This historical study using an ethnobiological approach discusses peasant subsistence strategies in Sweden in the eighteenth century using contemporary sources, which provide an opportunity to study how the population obtained foodstuffs, adapted their diet to available ingredients, and the interaction and conflicting views of peasants and scientists about new, science-based nutrition proposals.

Active Object Detection and Tracking Using Gimbal Mechanisms for Autonomous Drone Applications

Object recognition, localization, and tracking play a role of primordial importance in computer vision applications. However, it is still an extremely difficult task, particularly in scenarios where objects are attended to using fast-moving UAVs that need to robustly operate in real time. Typically the performance of these vision-based systems is affected by motion blur and geometric distortions, to name but two issues. Gimbal systems are thus essential to compensate for motion blur and ensure visual streams are stable. In this work, we investigate the advantages of active tracking approaches using a three-degrees-of-freedom (DoF) gimbal system mounted on UAVs. A method that utilizes joint movement and visual information for actively tracking spherical and planar objects in real time is proposed. Tracking methodologies are tested and evaluated in two different realistic Gazebo simulation environments: the first on 3D positional tracking (sphere) and the second on tracking of 6D poses (planar fiducial markers). We show that active object tracking is advantageous for UAV applications, first, by reducing motion blur, caused by fast camera motion and vibrations, and, second, by fixating the object of interest within the center of the field of view and thus reducing re-projection errors due to peripheral distortion. The results demonstrate significant object pose estimation accuracy improvements of active approaches when compared with traditional passive ones. More specifically, a set of experiments suggests that active gimbal tracking can increase the spatial estimation accuracy of known-size moving objects, under conditions of challenging motion patterns and in the presence of image distortion.

Korean Syntactic Complexity Analyzer (KOSCA): An NLP application for the analysis of syntactic complexity in second language production

Given the lack of computational tools available for assessing second language (L2) production in Korean, this study introduces a novel automated tool called the Korean Syntactic Complexity Analyzer (KOSCA) for measuring syntactic complexity in L2 Korean production. As an open-source graphic user interface (GUI) developed in Python, KOSCA provides seven indices of syntactic complexity, including traditional and Korean-specific ones. Its validity was tested by investigating whether the syntactic complexity indices measured by it in L2 written and spoken production could explain the variability of L2 Korean learners’ proficiency. The results of mixed-effects regression analyses showed that all seven indices significantly accounted for learner proficiency in Korean. Subsequent stepwise multiple regression analyses revealed that the syntactic complexity indices explained 56.0% of the total variance in proficiency for the written data and 54.4% for the spoken data. These findings underscore the validity of the syntactic complexity indices measured by KOSCA as reliable indicators of L2 Korean proficiency, which can serve as a valuable resource for researchers and educators in the field of L2 Korean learning and assessment.

Surface‐Enhanced Raman Scattering in BIC‐Driven Semiconductor Metasurfaces

AbstractSemiconductor‐based surface‐enhanced Raman spectroscopy (SERS) substrates, as a new frontier in the field of SERS, are hindered by their poor electromagnetic field confinement and weak light‐matter interaction. Metasurfaces, a class of 2D artificial materials based on the electromagnetic design of nanophotonic resonators, enable strong electromagnetic field enhancement and optical absorption engineering for a wide range of semiconductors. However, the engineering of semiconductor substrates into metasurfaces for improving SERS activity remains underexplored. Here, an improved SERS metasurface platform is developed that leverages the combination of titanium oxide (TiO2) and the emerging physical concept of optical bound states in the continuum (BICs) to boost the Raman emission. Moreover, fine‐tuning of BIC‐assisted resonant absorption offers a pathway for maximizing the photoinduced charge transfer effect (PICT) in SERS. High values of BIC‐assisted electric field enhancement (|E/E0|2 ≈103) are achieved, challenging the preconception of weak electromagnetic (EM) field enhancement on semiconductor SERS substrates. The BIC‐assisted TiO2 metasurface platform offers a new dimension in spectrally‐tunable SERS with earth‐abundant and bio‐compatible semiconductor materials, beyond the traditional plasmonic ones.

Gesture-Based Interactions: Integrating Accelerometer and Gyroscope Sensors in the Use of Mobile Apps

This study investigates the feasibility and functionality of accelerometer and gyroscope sensors for gesture-based interactions in mobile app user experience. The core of this innovative approach lies in introducing a dynamic and intuitive user interaction model with the device sensors. The Android app developed for this purpose has been created for its use in controlled experiments. Methodologically, it was created as a stand-alone tool to both capture quantitative (time, automatically captured) and qualitative (behavior, collected with post-task questionnaires) variables. The app’s setting features a set of modules with two levels each (randomized presentation applied, minimizing potential learning effects), allowing users to interact with both sensor-based and traditional touch-based scenarios. Preliminary results with 22 participants reveal that tasks involving sensor-based interactions tend to take longer to complete when compared to the traditional ones. Remarkably, many participants rated sensor-based interactions as a better option than touch-based interactions, as seen in the post-task questionnaires. This apparent discrepancy between objective completion times and subjective user perceptions requires a future in-depth exploration of factors influencing user experiences, including potential learning curves, cognitive load, and task complexity. This study contributes to the evolving landscape of mobile app user experience, emphasizing the benefits of considering the integration of device sensors (and gesture-based interactions) in common mobile usage.