Regular Items Research Articles

Important Regulatory Guidelines on Natural Products

Abstract: Ayurvedic cosmeceuticals are alluded to as products of various passable magnificence substances to shape the base in which one or more ayurvedic parts are utilized to give benefits and various ailments. The Drugs and Cosmetics Act of 1940 controls the approaches concerning the making, dealing, amassing, allotment, and importing of drugs in essentially a comparable manner to radiance care things in India. Quality control and assessment of Ayurvedic drugs must ensure the effectiveness of the drug. Given their crucial role, it involves evaluating their physical, chemical, and physiochemical qualities, as well as conducting in-vitro and in-vivo tests. Natural ingredients have consistently been our primary source of medicines, and dosage forms determine how drug molecules or plant components are delivered to the site of action within the body. Good agricultural and collection practices (GACP) rules have been given by the WHO (World Health Organization) for the differentiation and planning of regular items. There are primarily two legal regulatory bodies within the AYUSH (Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy) sector i.e., Central Council of Indian Medicine (CCIM) and the Central Council of Homeopathy.

Comparative Study of Catalysis Strategies: Friedel-Crafts Alkylation Vs. Michael's Addition of Indoles to Nitroalkenes

Indoles are critical in natural amalgamation for their flexible jobs in drugs, regular items, and material science, exhibiting huge pharmacological and compound reactivity. Due to their versatility and high reactivity, nitroalkenes are essential electrophilic partners in organic synthesis. While indoles and nitroalkenes are used in both Michael addition and Friedel-Crafts alkylation for producing carbon-carbon bonds, the catalyst types and reactions involved are different. Michael addition employs conjugate addition, whereas Friedel-Crafts alkylation employs electrophilic aromatic substitution. Each technique has a different level of selectivity and distinct synthetic applications. This review examines the advancements and persistent challenges in catalysis, focusing on the comparative methodologies of Friedel-Crafts alkylation and Michael addition involving indoles and nitroalkenes. Emphasizing green chemistry principles, it discusses the potential for sustainable and efficient synthetic processes through the use of innovative catalysts, including photocatalysis and biocatalysis. The integration of computational studies and interdisciplinary collaboration is essential for developing economically viable and environmentally responsible chemical synthesis, ultimately contributing to the creation of advanced materials and pharmaceuticals.

Comparative Study on Catalysis Strategies: Friedel-Crafts Alkylation vs. Michael Addition of Indoles to Nitroalkenes

Indoles are critical in natural amalgamation for their flexible jobs in drugs, regular items, and material science, exhibiting huge pharmacological and compound reactivity. Due to their versatility and high reactivity, nitroalkenes are essential electrophilic partners in organic synthesis. While indoles and nitroalkenes are used in both Michael addition and Friedel-Crafts alkylation for producing carbon-carbon bonds, the catalyst types and reactions involved are different. Michael addition employs conjugate addition, whereas Friedel-Crafts alkylation employs electrophilic aromatic substitution. Each technique has a different level of selectivity and distinct synthetic applications. This review aims to examine the advancements and persistent challenges in catalysis, focusing on the comparative methodologies of Friedel-Crafts alkylation and Michael addition involving indoles and nitroalkenes. Emphasizing green chemistry principles, it discusses the potential for sustainable and efficient synthetic processes through the use of innovative catalysts, including photocatalysis and biocatalysis. The integration of computational studies and interdisciplinary collaboration is essential for developing economically viable and environmentally responsible chemical synthesis, ultimately contributing to the creation of advanced materials and pharmaceuticals.

Reconciling category exceptions through representational shifts.

Real-world categories often contain exceptions that disobey the perceptual regularities followed by other members. Prominent psychological and neurobiological theories indicate that exception learning relies on the flexible modulation of object representations, but the specific representational shifts key to learning remain poorly understood. Here, we leveraged behavioral and computational approaches to elucidate the representational dynamics during the acquisition of exceptions that violate established regularity knowledge. In our study, participants (n = 42) learned novel categories in which regular and exceptional items were introduced successively; we then fitted a computational model to individuals' categorization performance to infer latent stimulus representations before and after exception learning. We found that in the representational space, exception learning not only drove confusable exceptions to be differentiated from regular items, but also led exceptions within the same category to be integrated based on shared characteristics. These shifts resulted in distinct representational clusters of regular items and exceptions that constituted hierarchically structured category representations, and the distinct clustering of exceptions from regular items was associated with a high ability to generalize and reconcile knowledge of regularities and exceptions. Moreover, by having a second group of participants (n = 42) to judge stimuli's similarity before and after exception learning, we revealed misalignment between representational similarity and behavioral similarity judgments, which further highlights the hierarchical layouts of categories with regularities and exceptions. Altogether, our findings elucidate the representational dynamics giving rise to generalizable category structures that reconcile perceptually inconsistent category members, thereby advancing the understanding of knowledge formation.

Natural products in neuroprotective therapies: Experimental and cheminformatics approaches to manage neurological disorders

Neurological disorders (NDs) such as Alzheimer’s disease (AD), Parkinson’s disease (PD), epilepsy, despondency, and dementia have been evidenced as a rising concern among diverse geographical regions. Brain-related diseases are currently the main concern because they increase mortality and morbidity in the elderly. Regardless of the continual efforts by modern scientists to develop a promising pharmacological or surgical management, the outcome has not been satisfactory. Also, due to synthetic drugs’ associated side effects, scientists have taken the initiative to consider using natural compounds as an alternative. Hence, they obtain pretty effective results by using natural compounds. Natural ingredients are synthesized from a variety of plant and animal sources. These natural ingredients cure brain diseases through a variety of mechanisms. For effective medication advancement, the molecules must go through preliminary clinical systems that require some investment and significant speculation. In this situation, cheminformatics is fundamental in diminishing time and venture. Cheminformatics methods play a significant role in these issues, including 3-dimensional quantitative structure-activity relationship 3D-(QSAR), virtual screening, docking, molecular dynamic studies, and quantum chemical studies. The vital purpose of this study is to disclose different types of NDs and the neuroprotective effect of several natural products for experimental and cheminformatics-based therapy. Natural products like green tea, flavonoids, and ginseng are discussed as effective neuroprotective products. However, more investigation is expected to comprehend the better utilization of regular items in future exploratory and cheminformatics-based treatment for NDs.

Modified consistency dysphagia diet protocol for Pakistan: Development perspective

Background: Increased in life expectancy has led to the increased need for texture-modified foods for dysphagia patients, to maintain their nutrition status. At present clinical practices in Pakistan are marred with no standard diet protocols resulting in misunderstanding in recommended consistencies of both food and fluid, hence compromising patients’ safety, necessitating the work of dysphagia diet protocol. Objectives: To develop a dysphagia diet consistency protocol for Pakistan. Methods: A descriptive study recruited 16 Speech-Language Pathologists and dieticians from Rawalpindi & Islamabad using convenient sampling from October 2018 to March 2019. The sample included SLPs and dieticians working for at least 1 year with dysphagia patients. To ensure the process of standardization list of food and fluids was generated by the professionals to analyze the various food textures with the help of a viscometer that contributed to labeling and defining the textures. With the help of the International Dysphagia Diet Standardization Initiative Flow Test, Fork Drip Test, Spoon tilt test, Fork Pressure Test, Spoon Pressure Test, and Finger Test, a list of food and fluid items categorized into 8 levels which help the management of dysphagia patients in clinical practice. Results: The current study developed a dysphagia diet protocol and categorized 29 foods and fluids as per the IDDSI framework. 10 items were placed in level 0 (Thin). 2 items were placed in level 1 (slightly thick). 2 items were placed in 2 (mildly thick) 1 item was placed at level 3. Level 4 included 2 items. Level 5 included 3 items. Level 6 included 4 items and Level 7 included 6 regular daily food items. Conclusion: The study successfully developed a standardized dysphagia diet consistency protocol consisting of 29 commonly readily available and popular foods consumed by Pakistanis and placed these items under 8 levels of the International Dysphagia Diet Standardization Initiative (IDDSI) recommendations. Keywords: Dysphagia; food consistency; IDDSI; swallowing disorders; texture modification.

An Examination of the Role of Inverted Dark Tetrad Items on Structural Properties and Construct Validity

Abstract: The use of inverted items is under vigorous debate in psychometric research. However, especially in the field of the Dark Tetrad – a compound of the aversive yet subclinical traits Machiavellianism, narcissism, psychopathy, and sadism –, the use of items in which high endorsement indicates low levels appears promising to obtain more information about low scores on the four traits. In this preregistered research ( N = 500), we developed an alternative version of the Short Dark Tetrad (SD4) which – unlike the original SD4 – has a balanced set of regular and inverted items. Following the theory of utilizing inverted items, we demonstrate that more information (in the sense of item response theory) can be obtained from the newly devised Mixed SD4 (MSD4) as compared to the original SD4. Thereby, the scores of the MSD4 can be validly interpreted in the sense of the underlying traits’ theories (i.e., construct validity), and the SD4 and the MSD4 yield highly similar nomological networks. We conclude that including inverted items is advantageous for the assessment of the Dark Tetrad. More generally, we present this case as a demonstration that balanced item sets are necessary to capture traits and behaviors exhaustively.

Food provision in Australian aged care homes does not meet protein needs of residents: A call for reform.

Malnutrition is common in older adults in aged care homes, partly due to inadequate protein intake. Menu planning guidelines are available however, adherence to guidelines is unknown. This study aimed to determine; (i) what are the average serving sizes of menu items provided and do they meet recommended portion sizes? (ii) does consumption from a 'typical' menu provide sufficient protein? and (iii) can substituting a 'typical' menu with high-protein options enable residents to achieve protein adequacy? This study involved 572 residents (73% female; aged 86.4 ± 7.3 years) from 60 aged-care homes in Australia involved in a 2-year cluster-randomised trial. During the trial, food intake was recorded quarterly using visual estimation of plate-waste and 42 061 foods analysed. As part of a secondary analysis of these data, portion sizes of foods were compared to guidelines by calculating the mean (95% confidence interval). Items were deemed inadequate if the upper 95% confidence interval remained below recommended portion sizes. On average 47% of breakfast and 80% of lunch/dinner items were below recommended portion sizes. Relative protein intakes, from a typical menu (most consumed foods), was 0.9 g and 0.8 g/kg body weight/day for females and males; both below recommendations. Substituting regular items with higher protein equivalents increased protein intake to 1.3 g and 1.2 g/kg body weight/day, for females and males, respectively. Aged care homes in Australia are not meeting menu planning guidelines resulting in insufficient protein being provided. Reform to menu guidelines including provision of high-protein foods, will ensure protein adequacy in older adults in aged-care homes.

Using Distance Measure to Perform Optimal Mapping with the K-Medoids Method on Medicinal Plants, Aromatics, and Spices Export

About 80% of the world's medicinal plants grow in Indonesia. The Negeri Rempah Foundation also said that Indonesia has more kinds of spices than any other country in Southeast Asia. To figure out the best way to export plants, you need to do a study that groups them by their main destination country. This is called "clustering," and it can be done by doing regional mapping. In the clustering process, measuring deviation/distance or distance space is a key part of figuring out how similar or regular data and items are. K-Medoids is one way to group things together. K-Medoids is an algorithm that groups data based on how far apart they are. Distance Measure is a way to measure the distance between two points. It can help an algorithm sort object into groups based on how similar their variables are. The dataset used comes from the Customs Documents of the Directorate General of Customs and Excise on the official website of the Central Bureau of Statistics for the period of 2012-2021 about the Export of Medicinal, Aromatic, and Spices Plants. This study uses mixed measures (mixed euclideandistance), numerical measures (camberradistance), and bregmandivergences (generalizeddivergence). The mapping results are compared with the validation of the Davies Bouldin Index (DBI). With the help of the rapidminer software, a number of tests were done. The results showed that using mixed measures (mixed euclideandistance) with a value of k=4 gave a DBI value of 0.021. Because it gives a DBI value close to 0, the K-Medoids algorithm with mixed measures (mixedeuclideandistance) is thought to work better than other distance measures.

Digital Nudge Stacking and Backfiring: Understanding Sustainable E-Commerce Purchase Decisions

Abstract Background: The consumption of ‘fast fashion’, which is expedited by cost-effective e-commerce systems, represents one of the major factors contributing to the acceleration of climate change. An emerging approach to steer consumers in the direction of more sustainable purchase decisions is digital nudging. This paper explores digital nudging in the context of green fashion e-commerce by testing the effectiveness of two nudging strategies on the decision to choose green fashion products (GFP) over regular fashion items. Method: This study was conducted as a between-subject online experiment (n=320) with four conditions simulating an e-commerce scenario. The participants were presented with different products: one was ecologically friendly, and another was the regular option. Depending on their randomized group allocation, the participants experienced a default nudge, a social norm nudge, a combination of both strategies, or no nudge. In addition, we conducted 10 qualitative interviews to gain a deeper understanding of consumers’ decision process. Results: Our experiment failed to demonstrate statistically significant relationships between the various nudging strategies and GFP purchase decisions. However, additional explorative analyzes confirmed a backfire effect for the combination of nudging strategies. This reveals the previously overlooked influence of participants’ identification on the effectiveness of digital nudging strategies. In addition, qualitative interviews revealed individual factors that influence sustainable e-commerce purchase decisions. Conclusion: This study contributes to information systems research by explaining the differences in the effectiveness of different nudging strategies regarding high-involvement compared to low-involvement products. Moreover, it provides empirical evidence of a backfire effect resulting from a combination of digital nudging strategies (i.e., digital nudge stacking). Finally, the study underscores the leverage that individual factors have on both GFP purchase decision and the effectiveness of nudges.

Smart nesting: estimating geometrical compatibility in the nesting problem using graph neural networks

Reducing material waste and computation time are primary objectives in cutting and packing problems (C &P). A solution to the C &P problem consists of many steps, including the grouping of items to be nested and the arrangement of the grouped items on a large object. Current algorithms use meta-heuristics to solve the arrangement problem directly without explicitly addressing the grouping problem. In this paper, we propose a new pipeline for the nesting problem that starts with grouping the items to be nested and then arranging them on large objects. To this end, we introduce and motivate a new concept, namely the Geometrical Compatibility Index (GCI). Items with higher GCI should be clustered together. Since no labels exist for GCIs, we propose to model GCIs as bidirectional weighted edges of a graph that we call geometrical relationship graph (GRG). We propose a novel reinforcement-learning-based framework, which consists of two graph neural networks trained in an actor-critic-like fashion to learn GCIs. Then, to group the items into clusters, we model the GRG as a capacitated vehicle routing problem graph and solve it using meta-heuristics. Experiments conducted on a private dataset with regularly and irregularly shaped items show that the proposed algorithm can achieve a significant reduction in computation time (30% to 48%) compared to an open-source nesting software while attaining similar trim loss on regular items and a threefold improvement in trim loss on irregular items.

Data Anomaly Detection through Semisupervised Learning Aided by Customised Data Augmentation Techniques

Structural health monitoring (SHM) systems may suffer from multiple patterns of data anomalies. Anomaly detection is an essential preprocessing step prior to the use of monitoring data for structural condition assessment or other decision making. Deep learning techniques have been extensively used for automatic category classification by training the network with labelled data. However, because the SHM data are usually large in quantity, manually labelling these abnormal data is time consuming and labour intensive. This study develops a semisupervised learning-based data anomaly detection method using a small set of labelled data and massive unlabelled data. The MixMatch technique, which could mix labelled and unlabelled data using MixUp, is adopted to enhance the generalisation and robustness of the model. A unified loss function is defined to combine information from labelled and unlabelled data by incorporating consistency regularisation, entropy minimisation, and regular model regularisation items. In addition, customised data augmentation strategies for time series are investigated to further improve the model performance. The proposed method is applied to the SHM data from a real bridge for anomaly detection. Results demonstrate the superior performance of the developed method with very limited labelled data, greatly reducing the time and cost of labelling efforts compared with the traditional supervised learning methods.

Two measures are better than one: combining iconicity ratings and guessing experiments for a more nuanced picture of iconicity in the lexicon

AbstractIconicity in language is receiving increased attention from many fields, but our understanding of iconicity is only as good as the measures we use to quantify it. We collected iconicity measures for 304 Japanese words from English-speaking participants, using rating and guessing tasks. The words included ideophones (structurally marked depictive words) along with regular lexical items from similar semantic domains (e.g., fuwafuwa ‘fluffy’, jawarakai ‘soft’). The two measures correlated, speaking to their validity. However, ideophones received consistently higher iconicity ratings than other items, even when guessed at the same accuracies, suggesting the rating task is more sensitive to cues like structural markedness that frame words as iconic. These cues did not always guide participants to the meanings of ideophones in the guessing task, but they did make them more confident in their guesses, even when they were wrong. Consistently poor guessing results reflect the role different experiences play in shaping construals of iconicity. Using multiple measures in tandem allows us to explore the interplay between iconicity and these external factors. To facilitate this, we introduce a reproducible workflow for creating rating and guessing tasks from standardised wordlists, while also making improvements to the robustness, sensitivity and discriminability of previous approaches.

A Review on Novel Herbal Drug Delivery System and its Application

Abstract: Herbal medicines are nearest to the customary treatment approach than some other conventional or elective medication draws near. They have a few phytoconstituents which are known for their remedial impacts on the body and are utilized for numerous hundreds of years. At the point when researchers used to grow new medications, regular items have their exceptional favorable circumstances, for example, plenteous clinical encounters, and their one-of-¬a-kind assorted variety of chemical structures and organic exercises. Varieties of molecules of herbal origin have been isolated, characterized, and evaluated for pharmacological activity by the investigators. However, phytomolecules need to be appropriately formulated to facilitate their physiological target to give more precise results. This examination expects to audit the writing on natural preparations and to investigate the potential ways used to deliver them so that further development can be done on existing herbal molecules as well as new molecules.

Underwater Image Enhancement Method via Multi-Interval Subhistogram Perspective Equalization

Due to the selective attenuation of light in water, captured underwater images exhibit poor visibility and cause considerable challenges for vision tasks. The structural and statistical properties of different regions of degraded underwater images are damaged at different levels, resulting in a global nonuniform drift of the feature representation, causing further degradation of visual performance. To handle these issues, we present an underwater image enhancement method via multi-interval subhistogram perspective equalization to address the issues posed by underwater images. We estimate the degree of feature drifts in each area of an image by extracting the statistical characteristics of the image, using this information to guide feature enhancement to achieve adaptive feature enhancement, thereby improving the visual effect of degraded images. We first design a variational model that uses the difference between data items and regular items to improve the color correction performance of the method based on subinterval linear transformation. In addition, a multithreshold selection method, which adaptively selects a threshold array for interval division, is developed. Ultimately, a multi-interval subhistogram equalization method, which performs histogram equalization in each subhistogram to improve the image contrast, is presented. Experiments on underwater images with various scenarios demonstrate that our method significantly outperforms many state-of-the-art methods qualitatively and quantitatively.

Neural dynamics underlying the processing of implicit form-meaning connections: The dissociative roles of theta and alpha oscillations

Implicit learning plays an important role in the language acquisition. In addition to helping people acquire the form-level rules (e.g., the word order regularities), implicit learning can also facilitate the acquisition of word meanings (i.e., the establishment of connections between the word form and its meanings). Although some behavioral studies have explored the processing of implicit form-meaning connections, the neural dynamics underlying this processing remains unclear. Through examining whether participants could implicitly acquire the literal and metaphorical meanings of novel words, and applying the time-frequency analysis on the electroencephalogram (EEG) data collected in the testing phase, the neural oscillations corresponding to the processing of implicit form-literal and form-metaphorical meaning connections were explored. The results showed that participants in the experimental group could implicitly acquire the form-literal and form-metaphorical meaning connections after training, while participants in the control group who were not trained did not have access to such form-meaning connections. Meanwhile, during the processing of form-literal meaning connections, the greater suppression of alpha oscillations was induced by the testing items that follow the same rules as the training items (i.e., the regular testing items) in the experimental group, whereas the stronger enhancement of theta oscillations was elicited by the regular testing items in the experimental group during the processing of form-metaphorical meaning connections. Our study provides insights for understanding the processing of implicit form-literal and form-metaphorical meaning connections and the neural dynamics underlying the processing.

Why Do Regular and Reversed Items Load on Separate Factors? Response Difficulty vs. Item Extremity

When constructing measurement scales, regular and reversed items are often used (e.g., “I am satisfied with my job”/“I am not satisfied with my job”). Some methodologists recommend excluding reversed items because they are more difficult to understand and therefore engender a second, artificial factor distinct from the regular-item factor. The current study compares two explanations for why a construct’s dimensionality may become distorted: response difficulty and item extremity. Two types of reversed items were created: negation items (“The conditions of my life are not good”) and polar opposites (“The conditions of my life are bad”), with the former type having higher response difficulty. When extreme wording was used (e.g., “excellent/terrible” instead of “good/bad”), negation items did not load on a factor distinct from regular items, but polar opposites did. Results thus support item extremity over response difficulty as an explanation for dimensionality distortion. Given that scale developers seldom check for extremity, it is unsurprising that regular and polar opposite items often load on distinct factors.

Constraints on Ease of Articulation in the Phonetics of Israeli Hebrew Casual Speech

Abstract: In the casual speech register, speakers naturally tend to facilitate ease of articulation, usually through processes of assimilation, reduction and elision, occasionally by insertion of certain vowels or consonantal glides. Such processes of assimilation, reduction or elision usually affect elements perceived to be weak, or minimal, and whose presence is not truly required (phonetically, or semantically), or that are easily recoverable from the context. There are, however, constraints on ease of articulation processes, preventing them from violating certain phonetic restrictions. There are also independent considerations that prevent reduction, elision or assimilation if they may affect significant semantic distinctions that are too essential to ignore. Thus, for instance, there exists a preference for secondary stress assignment resulting in alternating rhythm of stressed and unstressed syllables in connected Hebrew speech; the configuration realigns itself in cases of vowel deletion, or when a "minimal" vowel is inserted to prevent sonority-hierarchy violations, or when a "stress clash" arises, and one of the syllables may need to be destressed to accommodate the alternating stress rhythm. However, another constraint assures that no destressing of the main stress of regular lexical items occur if the word concerned cannot easily be reconstructed from the context. Furthermore, no shifting is allowed in the placement of the main lexical stress, unless it is a function word or a very frequent, easily identified lexical item. A few phonetic constraints will be discussed in some detail, as well as semantic ones reassuring that the processing of meaning will not be negatively affected by phonetic "ease-of-articulation" processes.

International Business Law Concerning Domestic and an International Trade

Law is the core discipline of society as well as playing a vital role in any organization which is working and exists in the World. International law and trade are the backbones of global organizations. In this present discussion, secondary data was used. Data were obtained from secondary sources, especially from the law discipline research article, and from authentic and reliable sources. In the research article, the law oriented international organizations were the main targeted respondents. The importance of the law is because there are many motivations behind why countries and individuals decide to exchange and carry on with work globally instead of confining themselves in an undertaking to secure homegrown industry. Motivations to exchange incorporate the need to acquire normal assets, items, or administrations, in any case, inaccessible locally; the craving to get similar items more inexpensively than the expense of locally delivered merchandise; the longing to accomplish a monetary advantage by sending out homegrown regular assets, items or administrations which pay for the expense of imports; the longing to assist less beneficial countries with accomplishing advancement; and the need to keep up with military or political partnerships with exchanging countries. The present study gives an outline of international exchanges and business law and the various homegrown and global associations engaged with the guideline of worldwide exchange. It likewise suggests a synopsis of the modalities of the development of an arrangement for the global exchanging of a decent, involving the advantages and entanglements of undertaking worldwide deals.

The Immigration Issue and the vox Populi: Letters to the Editor in six Scandinavian Newspapers 1970–2016

ABSTRACT Letters to the editor are argued to be a staple of the public sphere and, by providing regular citizens with a platform to voice their concerns to a large audience, a central democratic function of a liberal press. However, the actual weight given by the press to citizens’ deliberation on issues and the contribution of these letters in terms of content is still little researched, and historical and comparative studies are largely absent. In this article we offer a case study of letters on the immigration issue in six Scandinavian newspapers (N = 1065). Charting their volume and content using content analysis and comparing them to the more elite-dominated columns and regular news items (N = 3264), we identify major historical and national variations in the salience of the issue and the weight given the vox populi in the press. Constructing a discursive space of immigration letters using multiple correspondence analysis and subsequent clustering into seven categories of letters, we identify a historical movement towards more problematizing and cultural discourse, strongest in the Danish newspapers. We also identify Sweden as a particularly interesting case, with fewer letters and less difference between letters and other newspaper content, for which we suggest some hypotheses.