Transformer models have emerged as frontrunners in the field of natural language processing, primarily due to their adept use of self-attention mechanisms to grasp the semantic linkages between words in sequences. Despite their strengths, these models often face challenges in single-task learning scenarios, particularly when it comes to delivering top-notch performance and crafting strong latent feature representations. This challenge is more pronounced in the context of smaller datasets and is particularly acute for under-resourced languages such as Arabic. In light of these challenges, this study introduces a novel methodology for text classification of Arabic texts. This method harnesses the newly developed Reverse Positional Encoding (RPE) technique. It adopts inductive-transfer learning (ITL) framework combined with a switching self-attention shared encoder, thereby increasing the model's adaptability and improving its sentence representation accuracy. The integration of Mixture of Experts (MoE) and Reverse Positional Encoding (RPE) techniques empowers the model to process longer sequences more effectively. This enhancement is notably beneficial for Arabic text classification, adeptly supporting both the intricate five-point and the simpler ternary classification tasks. The empirical evidence points to its outstanding performance, achieving accuracy rates of 87.20% for the HARD dataset, 72.17% for the BRAD dataset, and 86.89% for the LABR dataset, as evidenced by the assessments conducted on these datasets.

In the realm of the five-category classification endeavor, there has been limited exploration into applied techniques for classifying Arabic text. These methods have primarily leaned on singletask learning, incorporating manually crafted features that lack robust sentence representations. Recently, the Transformer paradigm has emerged as a highly promising alternative. However, when these models are trained using single-task learning, they often face challenges in achieving outstanding performance and generating robust latent feature representations, especially when dealing with small datasets. This issue is particularly pronounced in the context of the Arabic dialect, which has a scarcity of available resources. Given these constraints, this study introduces an innovative approach to dissecting sentiment in Arabic text. This approach combines Inductive Transfer (INT) with the Transformer paradigm to augment the adaptability of the model and refine the representation of sentences. By employing self-attention SE-A and feed-forward sub-layers as a shared Transformer encoder for both the five-category and three-category Arabic text classification tasks, this proposed model adeptly discerns sentiment in Arabic dialect sentences. The empirical findings underscore the commendable performance of the proposed model, as demonstrated in assessments of the Hotel Arabic-Reviews Dataset, the Book Reviews Arabic Dataset, and the LARB dataset.

In recent times, models like the Transformer have showcased remarkable prowess in tasks related to natural language processing. However, these models tend to be excessively intricate and demand extensive training. Additionally, while the multi-head self-attention mechanism in the Transformer model aims to capture semantic connections between words in a sequence, it encounters limitations when handling short sequences, thereby limiting its effectiveness in 5-polarity Arabic sentiment analysis tasks. The switch-transformer model has recently emerged as a high-performing alternative. Nevertheless, when these models are trained using single-task learning, they often fall short of achieving exceptional performance and struggle to generate robust latent feature representations, especially when working with compact datasets. This challenge is particularly pronounced in the case of the Arabic dialect, which is considered a low-resource language. Given these constraints, this research introduces a novel approach to sentiment analysis in Arabic text. This method leverages multitask learning in tandem with the switch-transformer shared encoder to enhance model adaptability and refine sentence representation. By introducing a mixture of expert (MoE) mechanism that break down the problem into smaller, more manageable sub-problems, the model becomes adept at handling lengthy sequences and intricate input-output relationships, benefiting both five-point and three-polarity Arabic sentiment analysis tasks. This proposed model effectively discerns sentiment in Arabic dialect sentences. The empirical results highlight the outstanding performance of the suggested model, as evidenced in evaluations on the Hotel Arabic-Reviews Dataset, the Book Reviews Arabic Dataset, and the LARB dataset.

Educational institutions must identify students who are academically struggling to provide them with necessary support to improve their performance. In this context, recommendation systems powered by deep learning techniques are vital for detecting and categorizing such students. These systems help students plan their future by uncovering patterns in their historical academic data. This study introduces a new deep learning model designed to classify academically underperforming students in educational settings. The model incorporates a Gated Recurrent Neural Network (GRU) and includes specific neural network features like a dense layer, max-pooling layer, and the ADAM optimization algorithm. The model's training and evaluation were conducted using a dataset comprising 15,165 student assessment records from various academic institutions. The performance of the developed GRU model was benchmarked against other educational recommendation systems, including Recurrent Neural Network models, AdaBoost, and the Artificial Immune Recognition System v2. The proposed GRU model demonstrated remarkable accuracy, achieving an overall rate of 99.70%.

This article proposes the use of intranasal rifampin as a means to improve protein homeostasis and disaggregate misfolded proteins in the age-related neurodegenerative proteinopathies. Alzheimer’s disease, Parkinson’s disease, multi-system atrophy, Lewy body dementia, frontotemporal dementia, amyotrophic lateral sclerosis and Huntington’s disease are all, at the core, proteinopathies. Although these diseases varying greatly in the specific disease-associated proteins, anatomic sites of the abnormal protein deposition and clinical presentations, what they have in common is disruption of normal “housekeeping” functions related to protein homeostasis, proteostasis. The prospect of pharmacologically augmenting autophagic capacity with a known drug repurposed to improve proteostasis is attractive; to accomplish these ends with an inexpensive drug with relative ease of delivery adds to the attractiveness. Rifampin can be delivered to the brain via the intranasal route. Rifampin has been used for decades primarily against mycobacterial infection; it has been given with intravenous, oral, intrathecal and topical routes including as eyedrops and nasal spray. Rifampin disaggregates toxic oligomers in vitro; given intranasally, rifampin improves memory and clears pathologic proteins in animal models of the proteinopathies. Rifampin acts as both a gatekeeper and a housekeeper against the abnormal proteins of these diseases. This article suggests the merit of a clinical trial with intranasal rifampin to boost protein homeostasis in the most common age-related neurodegenerative proteinopathy, Alzheimer’s disease. The primary outcome of such a trial is change in risk of Alzheimer’s pathology as measured by plasma-based amyloid peptide 42/40 testing pretreatment and follow-up testing after 6 months of intranasal rifampin.

The Bacillus Calmette-Guérin (BCG) vaccine has been used for over one hundred years to protect against the most lethal infectious agent in human history, tuberculosis. Over four billion BCG doses have been given and, worldwide, most newborns receive BCG. A few countries, including the United States, did not adopt the WHO recommendation for routine use of BCG. Moreover, within the past several decades, most of Western Europe and Australia, having originally employed routine BCG, have discontinued its use. This review article articulates the impacts of those decisions. The associated consequences include increased tuberculosis, increased infections caused by non-tuberculous mycobacteria (NTM), increased autoimmune disease (autoimmune diabetes and multiple sclerosis) and increased neurodegenerative disease (Parkinson’s disease and Alzheimer’s disease). This review also offers an emerged zoonotic pathogen, Mycobacterium avium ss. paratuberculosis (MAP) as a mostly unrecognized NTM that may have a causal role in some, if not all, of these diseases. Current clinical trials with BCG for varied infectious, autoimmune and neurodegenerative diseases have brought this century-old vaccine to the fore due to its presumed immuno-modulating capacity. With its historic success and strong safety profile, the new and novel applications for BCG may lead to its universal use –putting the Western World back onto the road not taken.

Over the past decades, overweight and obesity has become a global epidemic and the leading threat for death. To prevent the serious risk, an overweight or obese individual must apply a long-term weight-management strategy to control food intake and physical activities, which is however, not easy. Recently, with the advances of information technology, more and more people can use wearable devices and smartphones to obtain physical activity information, while they can also access various health-related information from Internet online social networks (OSNs). Nevertheless, there is a lack of an integrated approach that can combine these two methods in an efficient way. In this paper, we address this issue and propose a novel mobile-social framework for health recognition and recommendation, namely, H-Rec². The main ideas of H-Rec² include (1) to recognize the individual's health status using smartphone as a general platform, and (2) to recommend physical activity and food intake based on personal health information, life science principles, and health-related information obtained from OSNs. To demonstrate the potentials of the H-Rec² framework, we develop a prototype that consists of four important components: (1) an activity recognition module that senses physical activity using accelerometer, (2) a health status modeling module that applies a novel algorithm to generate personalized health status index, (3) a restaurant information collection module that collects relevant information from OSN, and (4) a restaurant recommendation module that provides personalized and context-aware recommendation. To evaluate the prototype, we conduct both objective and subjective experiments, which confirm the performance and effectiveness of the proposed system.

Recent studies have demonstrated silk fibroin’s ability to extend the shelf life of foods by mitigating the hallmarks of spoilage, namely oxidation and dehydration. Due to the potential for this protein to become more widespread, its safety was evaluated comprehensively. First, a bacterial reverse mutation test (Ames test) was conducted in five bacterial strains. Second, an in vivo erythrocyte test was conducted with Sprague Dawley rats at doses up to 1,000mg/kg-bw/day. Third, a range-finder study was conducted with Sprague Dawley rats at the highest consumption amount given solubility and oral gavage volume constrains (500mg/kg-bw/day). Fourth, a 28-day study in Sprague Dawley rats was conducted at the 500mg/kg-bw/day amount. Fifth, an in vitro pepsin digestion assay was performed to assess the potential for protein allergenicity. Sixth, allergenic potential was further assessed using liquid chromatography-mass spectroscopy for detection of allergenic insect proteins. Seventh, the protein sequences were subjected to bioinformatic analyses. Together, these studies raise no mutagenic, carcinogenic, toxicological, or allergenic concerns with the oral consumption of silk fibroin.

Purpose: To evaluate nursing leaders' perception towards communication and relationship management competencies while using digital platforms during the COVID-19 pandemic. Background: Communication and relationship management competencies among nursing leaders will ensure healthcare models are successfully implemented. Nursing leaders can achieve effective leadership by mastering these competencies leading to an overall improvement in the quality of nursing care. However, digital platforms have been rapidly evolving in the healthcare ecosystem and have been significant during the battle with COVID-19. It is crucial to ensure that nursing leaders can use digital platforms to communicate and practice efficient management in their op-erations, especially during a crisis when their services are vital. Design: Descriptive, comparative study. Methods: The study was conducted between February to March 2021. A 5-item Linkert-type questionnaire was adopted from the American Organization for Nursing Executives (2005) and was sent to identified nursing leaders in Hamad Medical Corporation through the official email. Results: Two hundred fifty nurse leaders were invited to participate, but only 116 responded positively, translating to a response rate of 46.4%. The male participants represented a larger proportion of 64.10%, while the female was 35.90%. Regarding the questionnaire, the Cronbach alpha was α ˃ 0.987, indicating that all items revealed a sufficient level of internal consistency. The respondents had a minimum of 0 and a maximum of 52.6n in the communication and relationship management items. Influencing behavior, relationship management, and effective communica-tion had the lowest scores, which indicate low competency. The F value in ANOVA analysis was close to 1.0, implying that the null hypothesis is true. The significance value is <0.5 implying that there is a difference in response on effective communication proficiency of nurse leaders. Conclusions: Digital platforms are communication tools that are widely adopted to engage and reach nurses on numerous topics. Nurse leaders should capitalize on their benefits and generate critical discussions. The continued need to research nursing leadership competencies is critical as healthcare continues to change and evolve. Educational institutions and healthcare organizations must understand that nursing leaders should strive for professional development and knowledge acquisition to improve their communication and management.

For most people, using social media to research products has become common. Despite previous research, there is a gap in understanding reviewers' product-related comments and how they lead to purchase intentions. In terms of contributions, this study analyses people's dependence on social media for product information in purchase intention while considering the moderating impact of risk and trust on the link between purchase intention and social media. The data were collected quantitatively using surveys. The sample consisted of 384 students. The study hypotheses were tested using the PROCESS macro after exploratory factor analysis and correlation analysis were conducted. Among those surveyed, it was confirmed that most people sought product-related comments on social media when seeking information about a product they might be interested in purchasing. It was also observed that the risk factor reduced the impact of other variables in the model presented in this study. In conclusion, this investigation is more reliable, and its outcomes benefit scholars, supervisors, merchants, and webmasters, for instance, in establishing a study for future research efforts and providing practical guidance that could boost promotional efforts and marketing activities, especially in this era of artificial intelligence.

This article introduces a novel payload structure, which has been experimentally proven to have smaller impact force while the carried internal electronics remains intact. The study describes in details how materials and geometric structures were chosen based on information analysis. It is clarified how possible geometric structures and materials can be chosen to yield optimal efficiency. Finite element method simulations were carried out to investigate the mechanical properties of several geometric structures, which has led to the dodecahedron form. For the frame, Polylactic Acid were chosen as an optimal material. A low air pressure test for parts of the structure, and also the whole structure were carried out with successful results. Drop tests, with force measuring sensors and high speed videos, were carried out for measuring and comparing the maximal impact force of classical payloads and the novel one. Laboratory and real life tests demonstrated that the developed new structure is safer and it is applicable.

In this paper, inspired by recent articles of G. Anatriello and G. Vincenzi (see \cite{Ana}), and G. Cerda-Morales (see \cite{Cer1,Cer2}), we will introduce the third-order $\overline{h}$-Jacobsthal and third-order $\overline{h}$-Jacobsthal--Lucas sequences and their associated quaternions. The new results that we have obtained extend most of those obtained in \cite{Cer2}.

Background: Crohn’s and Ulcerative Colitis Questionnaire-32 (CUCQ-32) is a validated questionnaire to measure the quality of life (QoL) in inflammatory bowel disease (IBD). However, it does not have stoma specific questions and can be lengthy. This study aimed to validate a subset of the CUCQ-32 that would be suitable for patients with a stoma. Methods: Baseline data were collected from a cohort of patients with acute ulcerative colitis who were participating in the CONSTRUCT multi-centre clinical trial. A subset of the CUCQ-32 questions was selected by stepwise regression. Further validation was examined using data from the UK IBD biological therapies audit. Construct validity was carried out using the EuroQol 5 dimensions (EQ5D) questionnaire, Simple Clinical Colitis Activity Index (SCCAI) and the Harvey-Bradshaw Index (HBI). Literature review and an expert focus group identified supplementary questions to cover patients with a stoma. Test-retest analysis was done during the patients’ second follow up visits. Results: Using the data from 124 patients, a short version questionnaire (CUCQ-12) was developed. Further validation using data from 484 patients with IBD as part of the UK IBD biological therapies audit. Using the data from 61 patients with a stoma, we identified 5 stoma specific questions for the CUCQ-12+. The CUCQ-12+ demonstrated excellent internal consistency (Cronbach’s α= 0.86); established effective reproducibility (intra-class correlation coefficient= 0.74); correlated well with the EQ5D (r= - 0.48), HBI (r= 0.45) and SCCAI (r= 0.43); and represented good responsiveness statistics (>0.5). Conclusions: CUCQ-12+ is a valid and reliable QoL measure that can be used for all patients with IBD in clinical practice including patients with a stoma.

We have investigated the antiferromagnetic phase transition in the frustrated and multiferroic hexagonal manganites $h$-(Y$_{0.98}$ Eu$_{0.02}$)MnO$_3$ (YEMO) and $h$-YMnO$_3$ (YMO). Elastic neutron scattering has been used to study in detail the phase transition in YMO and YEMO in zero pressure and in YMO at a hydrostatic pressure of 1.5~GPa. In zero pressure, we find the critical temperature $T_{\rm N} = 72.11(5)$~K and 71.3(1)~K and the critical exponent $\beta = 0.206(3)$ and 0.22(2), for YEMO and YMO, respectively. This is in agreement with earlier work by Roessli {\em et al.}. In applied hydrostatic pressure of 1.5~GPa, the ordering temperature increases to $T_{\rm N} = 75.2(5)$~K, in agreement with earlier reports, while $\beta$ is unchanged. Inelastic neutron scattering was used to determine the anisotropy spin wave gap at the phase transition, expected from spin wave theory to close with a critical exponent $\beta'$ identical to the one of the order parameter, $\beta' = \beta$. Our results indicate that the gap in YEMO indeed closes at $T_{\rm N}=72.4(3)$~K with $\beta' = 0.24(2)$, while the in-pressure gap in YMO closes at 75.2(5)~K with an exponent of $\beta' =0.19(3)$. In addition, the low-temperature anisotropy gap was found to have a slightly higher absolute value under pressure. The consistent values obtained for $\beta$ in the two systems support the likelihood of a new universality class for triangular, frustrated antiferromagnets.

The treatment of the bulky Rind-based dibromosilanes, (Rind)2SiBr2 (2) [Rind = 1,1,7,7-tetra-R1-3,3,5,5-tetra-R2-s-hydrindacen-4-yl: EMind (a: R1 = Et, R2 = Me) and Eind (b: R1 = R2 = Et)], with two equivalents of tBuLi in Et2O at low temperatures resulted in the formation of blue solutions derived from the diarylsilylenes, (Rind)2Si: (3). Upon warming the solutions above −20 °C, the blue color gradually faded, accompanying the decomposition of 3 and yielding the cyclic hydrosilanes (4) via intramolecular C−H bond insertion at the Si(II) center. The molecular structures of the bulky Eind-based 3b and 4b were confirmed by X-ray crystallography. Thus, at −20 °C, blue crystals were formed (Crystal-A), which were identified as mixed crystals of 3b and 4b. Additionally, colorless crystals of 4b as a singular component were isolated (Crystal-B), whose structure was also determined by an X-ray diffraction analysis. Although the isolation of 3 was difficult due to their thermally-labile nature, their structural characteristics and electronic properties were discussed based on the experimental findings complemented by computational results. We also examined the hydrolysis of 3b to afford the silanol, (Eind)2SiH(OH) (5b).

The human landscape transforming activity contributes to the global change of vegetation in different forms. Hunting is one of the most ancient human landscape-shaping activities. Feeders for hunting are particularly disruptive to vegetation. In the present study, we conducted a vegetation survey in these highly disturbed places. We are investigating the vegetation dynamics over several years in in the turkey oak–sessile oak zone, in two areas with different moisture and shade conditions (forest and clearing). One important background factor is changes in precipitation and temperature. The novelty of our present study lies in the fact that the observation takes place with continuous disturbance, where the human influence is very large. Our results confirm that the weed infestation be detectable at bait sites over a long period, and the interannual changes were typical in every year, according to the fact that in August, more weed species are usually present with a greater cover at the bait sites. The main meteorological factors played a role in the degree of weed infestation in each year. There was a higher proportion of vegetation regeneration in wetter years, while dry periods do not favor successional processes. With the drying of the climate, the disturbed areas are constantly losing their natural value, but wetter weather is not an automatic solution either. A more precise understanding of vulnerable systems and careful planning of treatment interventions is necessary.

We report on the occurrence of natural Magnesium Alumina Silicate Hydrate (M-(A)-S-H) cement at Feragen and Leka in eastern and western Trøndelag Norway, respectively. Both occurrences are located in the sub-arctic climate zone and form in glacial till and moraine material deposited on ultramafic rock during the Weichselian glaciation. Weathering of serpentinized peridotite dissolve brucite and result in a relative high pH alkaline fluid that subsequently reacts with the felsic minerals of the till (quartz, plagioclase, K-feldspar) to form a cement consisting of an amorphous material or a mixture of nanocrystalline Mg-rich phyllosilicates, including illite. The presence of plagioclase in the till results in the enrichment of alumina in the cement, i.e., forms M-A-S-H instead of the M-S-H cement. Dissolution of quartz results in numerous etch-pits and negative quartz crystals filled with M-A-S-H cement. Where the quartz dissolution is faster that the cement precipitation, a honeycomb-like texture is formed. Compositionally the cemented till (tillite) contains more MgO and has a higher loss of ignition than the till, suggesting that the cement is formed by a MgO fluid that previously reacted with the peridotite. The M-(A)-S-H cemented till represent a new type of duricrust, coined magsilcrete. The study of natural Mg-cement provides information on peridotites as a Mg-source for Mg-cement and as a feedstock for CO2 sequestration.

In this paper a full state feedback control of a double inverted pendulum on a cart (DIPC) are designed and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, difference between kinetic and potential energy of the DIPC system. A full state feedback control with H infinity and H 2 is addressed. Two approaches are tested: open loop impulse response and a double inverted pendulum on a cart with full state feedback H infinity and H 2 controllers. Simulations reveal superior performance of the double inverted pendulum on a cart with full state feedback H infinity controller.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In this data deposit, I describe a dataset that is the result of content mining 167,318 published articles for statistical test results. As a result of this content mining, 688,112 results from 50,845 articles were extracted. In order to provide a comprehensive set of data, the statistical results are supplemented with metadata from the article they originate from. The dataset is provided in a comma separated file (CSV) in long-format. For each of the 688,112 results, 20 variables are included, of which seven are article metadata and 13 pertain to the individual statistical results (e.g., reported and recalculated p-value). A five-pronged approach was taken to generate the dataset: (i) collect journal lists, (ii) spider journal pages for articles, (iii) download articles, (iv) add article metadata, and (v) mine articles for statistical results.

In this paper, we propose an imagined speech-based brain wave pattern recognition using deep learning. Multiple features were extracted concurrently from eight-channel Electroencephalography (EEG) signals. To obtain classifiable EEG data with fewer number of sensors, we placed the EEG sensors on carefully selected spots on the scalp. To decrease the dimensions and complexity of the EEG dataset and to avoid overfitting during the deep learning algorithm, we utilized the wavelet scattering transformation. A low-cost 8-channel EEG headset was used with MATLAB 2023a to acquire the EEG data. The Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) was used to decode the identified EEG signals into four audio commands: Up, Down, Left, and Right. Wavelet scattering transformation was applied to extract the most stable features by passing the EEG dataset through a series of filtration processes. Filtration has been implemented for each individual command in the EEG datasets. The proposed imagined speech-based brain wave pattern recognition approach achieved a 92.50% overall classification accuracy. This accuracy is promising for designing a trustworthy imagined speech-based Brain-Computer Interface (BCI) future real-time systems. For better evaluation of the classification performance, other metrics were considered, and we obtained 92.74%, 92.50% and 92.62% for precision, recall, and F1-score, respectively.

A modular approach to the construction of electric machines, drive systems, power supply systems is a new direction of modern technology development. Especially, the modular approach is promising for electric vehicles due to such positive aspects as increased efficiency, fault tolerance, overall reliability, safety, enhanced control capabilities, etc. In this work, the modular approach is comprehensively applied to an EV powertrain system, which includes a dual three-phase (DTP) BLDC motor with two machine modules of an asymmetric configuration, two battery modules and a supercapacitor module (SCM). The proposed H–H configuration of modular EV powertrain system includes four voltage source inverters that combine the power modules with the open ends of the windings (OEW) of the module machine armature, and provide control of their operation. Based on the developed mode system of the OEW machine module operation for EV traction and braking, a general control algorithm for the proposed configuration of the modular EV powertrain system has been developed. It combines the control of the operating modes with the functions of maintaining the required SOC level of the SCM and equalizing the SOCs of the two battery modules. The conducted simulation and experimental studies confirmed the workability and effectiveness of the proposed solutions.

Cystic Fibrosis is a chronic disease affecting multiple systems including the GI tract. Clinical manifestation in patients can start as early as infancy and vary across different age groups. With the advent of new highly effective modulators, the life expectancy of PwCF has improved significantly. Various GI aspects of CF care such as nutrition are linked to the overall improvement in morbidity, lung function, and quality of life of PwCF. The variable clinical presentations and management of GI diseases in pediatrics and adults CF should be recognized. Therefore, it is necessary to ensure efficient transfer of information between pediatric and adult providers for proper continuity of management and coordination of care at the time of transition. The transition of care is a challenging process for both patients and providers and currently, there are no specific tools for GI providers to help ensure smooth transition. In this review, we aim to highlight the crucial features of GI care at the time of transition and provide a checklist that can assist in ensuring an effective transition and ease the challenges associated with it.

In this paper, the design and analysis of coupled tank water level control system is done using robust control theory. The main aim of this work is to improve level controlling mechanisms in industries and household areas. In this paper, H ∞ and μ –synthesis controllers are designed to improve the level control system. The coupled tank water level control system is designed using the proposed controller’s comparison and tested for tracking a reference level signals (step, sine wave and random) and simulation results have been analyzed successfully. Finally the comparative simulation results prove the effectiveness of the proposed coupled tank water level control system with H ∞ controller for improving the tracking mechanism performance of the system.

In this work, we introduce the class of h-MN-convex functions by generalizing the concept of MN-convexity and combining it with h-convexity. Namely, let M : [0, 1] → [a, b] be a Mean function given by M (t) = M (t; a, b); where by M (t; a, b) we mean one of the following functions: A_t (a, b) := (1 − t) a + tb, G_t (a, b) = a^1−tb^t and H_t (a, b) := $\frac{ab}{ta+\left(1-t\right)b}=\frac{1}{A_t\left(\frac{1}{a},\frac{1}{b}\right)}$ with the property that M (0; a, b) = a and M (1; a, b) = b. Let I, J be two intervals subset of (0, ∞) such that (0, 1) ⊆ J and [a, b] ⊆ I. Consider a non-negative function h : J → (0, ∞), a function f : I → (0, ∞) is said to be h-MN-convex (concave) if the inequality f (M (t; x, y)) ≤ (≥) N (h(t); f (x), f (y)), holds for all x, y ∈ I and t ∈ [0, 1]. In this way, nine classes of h-MN-convex functions are established, and therefore some analytic properties for each class of functions are explored and investigated. Characterizations of each type are given. Various Jensen’s type inequalities and their converses are proved.

One of the main challenges of cultured meat is reducing the costs of production, often described as scaling. The main components of the cultivation process include: cells, media, scaffolds and bioreactors. This work presents an alternative to current stainless steel or glass bioreactors and uses food-grade plant-based scaffolds. Bioreactors must be sterile and leak-free to maintain a proper environment for cell growth. Thermoplastic films are a popular material for constructing these fluidic systems, but traditional methods of welding these film are expensive and do not allow rapid prototyping resulting in high research and development costs for companies. In this study, a laser welding method was developed to join thermoplastic films in a way that prevents contamination and leaks, affording effective macro-fluidics fabrication. This technique was tested using polyethylene (PET) films and a laser cutter operating with settings calibrated for the material to be welded or cut. The laser welding method was found to produce strong, leak-free seals in PET films with minimal heat-induced damage to the films. The ability to design fluidics, chambers and ports of various size. Using this method afforded the incorporation of plant-based scaffolds from food-grade plants (Rice). The laser welding method developed in this study provides a reliable, contamination-free method for the rapid fabrication of fluidic systems for cell cultivation. This technique has the potential to be compatible with a vast range of cell types and scaffolds and to be widely adopted in tissue engineering for regenerative medicine and food applications such as cultured meat.

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

This paper aims to unify q-derivative/q-integral and h-derivative/h-integral in a single definition, this will be called q−h-derivative/q−h-integral. These notions are further extended on finite interval [a,b] in the form of left and right q−h-derivatives and q−h-integrals. Some inequalities are studied for q−h-integrals which are directly connected with well known results. In diverse fields of science and engineering the theory based on q-derivatives/q-integrals and h-derivatives/h-integrals can be unified by using the concept of q−h-derivative/q−h-integral.

In this study, we define new classes of convexity called of h-Godunova-Levin and h-Godunova-Levin preinvexity, through which some new inequalities of Hermite-Hadamard type were established. These new classes are the generalisation of several known convexity including the s-convex, P-function, Godunova-Levin. Further, the properties of h-Godunova-Levin function were also discussed. Meanwhile, the applications of h-Godunova-Levin Preinvex function are given

In this work, several inequalities of Popoviciu type for h-MN-convex functions are proved, where M and N are denote to Arithmetic, Geometric and Harmonic means and h is a non-negative superadditive or subadditive function.

Renewable resources gain increasing interest as source for environmentally benign biomaterials, such as drug encapsulation/release compounds, and scaffolds for tissue engineering in regenerative medicine. Being the second largest naturally abundant polymer, the interest in lignin valorization for biomedical utilization is rapidly growing. Depending on resource and isolation procedure, lignin shows specific antioxidant and antimicrobial activity. Today, efforts in research and industry are directed toward lignin utilization as renewable macromolecular building block for the preparation of polymeric drug encapsulation and scaffold materials. Within the last five years, remarkable progress has been made in isolation, functionalization and modification of lignin and lignin-derived compounds. However, literature so far mainly focuses lignin-derived fuels, lubricants and resins. The purpose of this review is to summarize the current state of the art and to highlight the most important results in the field of lignin-based materials for potential use in biomedicine (reported in 2014–2018). Special focus is drawn on lignin-derived nanomaterials for drug encapsulation and release as well as lignin hybrid materials used as scaffolds for guided bone regeneration in stem cell-based therapies.

On the H-type group G⊂Rm×Rn, we study the existence of solutions for the Brezis-Nirenberg problem

Most Acinetobacter baumannii strains are naturally competent. Although some information is available about factors that enhance or reduce the frequency of transformation of this bacterium, the regulatory elements and mechanisms are barely understood. In this article, we describe studies on the role of H-NS in the regulation of expression of genes related to natural competency and the ability to uptake foreign DNA. The expression levels of the natural transformation-related genes pilA, pilT, pilQ, comEA, comEC, comF, and drpA were significantly increased in a Δhns derivative of Acinetobacter baumannii A118. Complementation of the mutant with a recombinant plasmid harboring hns restored expression levels of six of these genes (pilT remained expressed at high levels) to those of the wild-type strain. The transformation frequency of the A. baumannii A118 Δhns strain was significantly higher than that of the wild-type. Similar, albeit not identical, effects occurred when hns was deleted from the hypervirulent A. baumannii AB5075 strain. Reduction of gene expression in a few cases was not as pronounced as to reach wild-type levels, and expression of comEA was enhanced further. In conclusion, the expression of all seven transformation-related genes was enhanced after deleting hns in A. baumannii A118 and AB5075, and these modifications are accompanied by an increase in the cells’ transformability. The results demonstrate a role of H-NS in A. baumannii’s natural competence.

Introduction: The trophoblast derived angiogenic factors are considered to play an important role in the pathophysiology of various complications of pregnancy. The aim of this study was to establish relationship between concentrations of soluble Human Leukocyte Antigen-G (sHLA-G) in maternal serum and amniotic fluid at 16-22 weeks of gestation and the sonographic measurements of the fetal and placental growth. Materials and methods: sHLA-G in serum and amniotic fluid, as well as fetal biometric data and placental volume and perfusion indices were determined in 41 uncomplicated singleton pregnancies. Results: The sHLA-G levels were unchanged both in amniotic fluid and in serum during mid-pregnancy. The sHLA-G level in serum correlated positively with amniotic sHLA-G level (β=0.63, p<0.01). Significant correlation was found between serum sHLA-G level and abdominal measurement (β=0.41, p<0.05) and estimated fetal weight (β=0.41, p<0.05). The amniotic sHLA-G level and placental perfusion (VI: β = -0.34, p<0.01 and VFI: β = -0.44, p<0.01, respectively) were negatively interrelated. A low amniotic sHLA-G level was significantly associated with nuchal translucency (r = -0.102, p<0.05). Conclusions: sHLA-G assayed in amniotic fluid might be a potential indicator for placental function, whereas the sHLA-G level in serum can be a prognostic modality for feto-placental insufficiency.

Reactions in water between the Cu2(µ-EGTA) chelate (EGTA = ethylene-bis(oxyethyleneimino)tetraacetate(4-) ion) and 2,6-diaminopurine (Hdap) in molar ratios 1:1 and 1:2 yield only blue crystals of the ternary compound [Cu4(μ-EGTA)2(μ-H(N3)dap)2(H2O)2]·7H2O (1) that has been studied by single crystal X-ray diffractometry, various physical methods (thermal stability, spectral and magnetic properties), as well as DFT theoretical calculations. In the crystal, uncoordinated water is disordered. The tetranuclear complex molecule also has some irrelevant disorder in an EGTA-ethylene moiety. In the complex molecule, both bridging organic molecules act as binucleating ligands. There are two distorted five- (type 4+1) and two six- (type 4+1+1) Cu(II) centres. Each half EGTA acts as a tripodal tetradentate Cu(II) chelator, with mer-NO2+O(ether, distal) conformation. Hdap exhibits the tautomer H(N3)dap, with the dissociable H-atom on its less basic N-heterocyclic atom. These features favour the efficient cooperation between Cu-N7 or Cu-N9 bonds with appropriate O-EGTA atoms, as N6-H···O or N3-H···O interligand interactions respectively. Bridging role of both organics determines the tetranuclear dimensionality of the complex in 1. In this crystal, such molecules associate in zig-zag chains, built by alternating ,-interactions between the five- or six-atom rings of Hdap ligands of adjacent molecules. DFT theoretical calculations (using two different theoretical models and characterized by the quantum theory of “atoms in molecules”) reveal the importance of these ,-interactions between Hdap ligands, as well as that corresponding to the referred hydrogen bonds in the contributed tetranuclear molecule.

Today, more than 70 million tons of lignin are produced by the pulp and paper industry every year. However, the utilization of lignin as a source for chemical synthesis is still limited due to the complex and heterogeneous lignin structure. The purpose of this study was a selective photodegradation of industrially available kraft lignin in order to obtain appropriate fragments and building block chemicals for further utilization, e.g. polymerization. Thus, kraft lignin obtained from soft wood black liquor by acidification was dissolved in sodium hydroxide and irradiated at a wavelength of 254 nm with and without the presence of titanium dioxide in various concentrations. Analyses of the irradiated products via SEC showed decreasing molar masses and decreasing polydispersity indices over time. At the end of the irradiation period the lignin was depolymerised to form fragments as small as the lignin monomers. TOC analyses showed minimal mineralisation due to the depolymerisation process.

Infections contribute to carcinogenesis through inflammation-related mechanisms. It is well established that H. pylori infection is an etiological factor in gastric carcinogenesis. However, the mechanism through which H. pylori infection contributes to the development of gastric cancer has not been fully elucidated. H. pylori-associated chronic inflammation is linked to genomic instability via reactive oxygen and nitrogen species (RONS). In this article, we summarize the current knowledge of H. pylori-induced double strand breaks (DSBs). Further, we will provide mechanistic insight into how processing of oxidative DNA damage via base excision repair (BER) leads to double strand breaks (DSBs). We review the recent progress how H. pylori infection triggers NF-kB /iNOS versus NF-kB/nucleotide excision repair (NER) axis mediated DSBs to drive genomic instability. Taken together, this review discusses current findings related to DSBs and their implications for the mechanisms of DSB repair.

In this paper we obtain some inequalities of Hermite-Hadamard type for composite convex functions. Applications for AG, AH-h-convex functions, GA, GG, GH-h-convex functions and HA, HG, HH-h-convex function are given.

In this study, the degradable superhydrophobic Mg/P/Z/F/H (magnesi-um/poly(-caprolactone)/zinc oxide/1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFDTES)/ heating process) composite materials were prepared through one-step method for enhancing the corrosion resistance of AZ91D magnesium alloys. Electrochemical measurements showed that Mg/P/Z/F/H materials significantly improved the corrosion resistance of magnesium alloys in 3.5 wt.% NaCl. The self-cleaning, adhesion and stability tests suggested that Mg/P/Z/F/H composite materials had well self-cleaning properties, good adhesion strength and stability in wet atmosphere.

The antiradical and antimicrobial activity of lignin and lignin-based films are both of great interest for applications such as food packaging additives. The polyphenol structure of lignin in addition to the presence of O-containing functional groups is potentially responsible for these activities. This study used DPPH assays to discuss the antiradical activity of HPMC/lignin and HPMC/lignin/chitosan films. The scavenging activity (SA) of both binary (HPMC/lignin) and ternary (HPMC/lignin/chitosan) systems was affected by the percentage of the added lignin: the 5% addition showed the highest activity and the 30% addition had the lowest. Both, scavenging activity and antimicrobial activity are depending on the biomass source showing the following trend: organosolv of softwood > Kraft of softwood > organosolv of grass. Testing the antimicrobial activities of lignins and lignin-containing films showed high antimicrobial activities against gram-positive and gram-negative bacteria at 35 °C and at low temperatures (0-7 °C). Purification of kraft lignin has a negative effect on the antimicrobial activity while storage has positive effect. The lignin release in the produced films affected the activity positively and the chitosan addition enhances the activity even more for both gram-positive and gram-negative bacteria. Testing the films against spoilage bacteria that grow at low temperatures revealed the activity of the 30% addition on HPMC/L1 film against both B. thermosphacta and P. fluorescens while L5 was active only against B. thermosphacta. In HPMC/lignin/chitosan films the 5% addition exhibited activity against both B. thermosphacta and P. fluorescens.

Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.

The focus of our study was the changes in the composition of semi-natural dry grasslands in Hungary. Since these valuable habitats were created with the help of humans, their preservation also requires regular treatment. Our mowing experiment aimed to investigate the suppression of the native Calamagrostis epigejos L. Roth. In Hungary, in the Cserhát Mountains, eight permanent plots were mowed twice a year. The vegetation was sampled annually between 2001 and 2011. The effects of mowing were investigated with repeated measures analysis of variance (ANOVA). After 10 years, the C. epigejos cover of the mowed plots decreased significantly, from the initial average of 62.38 to 7.50%. Surprisingly, we also experienced a similar decrease in the control plots. Regular treatment also had a positive effect on the number of species and diversity. Species richness increased continuously in both treatment types, which indicates the combined effect of vegetation succession and treatment. The biomass growth of other Poaceae and Fabaceae species, which are important from a grassland management perspective, was also facilitated by mowing. Our results suggest that long-term in situ experiments and continuous botanical studies are needed to establish a reliable utilization of grasslands.

This paper addresses a mode-dependent state-feedback H∞ control for descriptor hybrid systems, considering both the absence and presence of actuator saturation. Firstly, the necessary and sufficient conditions for the stochastic admissibility criterion with H∞ performance ? of the closed-loop system is proposed. Given the proposed non-convex condition, the author reformulates it into linear matrix inequalities (LMIs). Then, to extend the result to the systems with actuator saturation, the actuator saturated control input is expressed as a linear combination of given state-feedback control input and a virtual control input that remains under the saturation level. To verify this expression, the set invariant condition is also suggested by using the singular mode-dependent Lyapunov function candidate. Therefore, the LMI conditions for the existence of the mode-dependent state-feedback H∞ control and the ellipsoidal shape of invariant set are successfully derived. Two numerical examples demonstrate the effectiveness of the proposed approach in optimizing H∞ performance $\gamma$ and identifying the largest invariant set.

The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.

In this paper, modelling designing and simulation of a Ward Leonard layout system is done using robust control theory. In order to increase the performance of the Ward Leonard layout system with H infinity optimal control synthesis and H infinity optimal control synthesis via gamma-iteration controllers are used. The open loop response of the Ward Leonard layout system shows that the system needs to be improved. Comparison of the Ward Leonard layout system with H∞ optimal control synthesis and H infinity optimal control synthesis via gamma-iteration controllers to track a desired step speed input have been done. Finally, the comparative simulation results prove the effectiveness of the proposed Ward Leonard layout system with H infinity optimal control synthesis controller in improving the percentage overshoot and the settling time.

Papain-like lysosomal cysteine proteases include 11 human cysteine cathepsins which act as endopeptidases and/or exopeptidases. They are involved in numerous physiological and pathological processes. Among them, only cathepsins B, H, C, and X/Z exhibit exopeptidase activity. Their activities are tightly regulated in various ways to prevent potentially hazardous effects on the cell. In this review, we focus on the structural and functional aspects of these four cysteine cathepsins and their role in neurodegeneration and cancer. Neurodegenerative disorders of aging share an endolysosomal dysfunction and accumulation and spread of oligomeric forms of neurotoxic proteins. The accumulation of various protein aggregates activates the microglia, thus inducing the activation and release of cysteine cathepsins and proinflammatory cytokines, leading to neurodegeneration. In cancer, cysteine cathepsins participate in tumor progression and metastasis. Tumor–stromal crosstalk leads to activation of the stroma and overexpression and secretion of proteolytic enzymes, triggering extracellular matrix degradation and the release of soluble factors. Activated stromal cells (i.e., macrophages, fibroblasts, mast cells) secrete additional growth factors, cytokines, and chemokines that are responsible for the regulation of processes leading to tumor progression and metastasis. Therefore, a better understanding of the role of cysteine cathepsins in neurodegeneration and cancer could lead to novel targeted therapeutic approaches.

In this paper, the design and control of a hydraulic system based tire changer machine have been analyzed and simulated using Matlab/Simulink Toolbox successfully. The machine have a displacement input which is a leg pedal displacement in order to push the piston of the pump to fed the motor with a pressured hydraulic fluid to rotate the tire with an angular speed to mount and dismount it. Augmentation based H_∞ and H₂ optimal synthesis controllers have been used to improve the performance of the machine. Comparison of the proposed controllers for tracking a reference input speed have been done using two reference inputs (step and random) signals. Finally the comparative simulation results proved the effectiveness of the proposed tire changer with H synthesis controller in improving the settling time and percentage overshoot.

Many corporations have now revised their value statements to showcase their commitment to sustainable development and green business due to the pressing issues of climate and environmental damage. Despite the importance of value statements that can direct companies to achieve sustainable goals, what kind of values can be perceived as organizational orientations to sustainability remains unknown. This study explores how the general public views the inclusion of sustainable components in value statements from the listed companies in Hong Kong by using Q-sort methodology (n = 30). Analyzing the final sample of 40 value statements extracted from 27 listed companies, we identified three factors related to sustainability, namely, Empowering business process management, Empowering customer-centric excellence, and Empowering sustainable progress. This study provides an additional component to the traditional triple bottom line by suggesting that internal operation of a company is an emerging idea to understand corporate sustainability.

The reaction of mercaptoacetic acid esters with pentachloro-2-nitro-1,3-butadiene provides appropriate precursors for the synthesis of 2,3,4-trisubstituted benzo[h]quinolines. These heterocycles are easily accessible via a single-step reaction with 1-naphthyl- or 1-anthracenylamine, respectively. Due to steric bulk and high electron density ring closure to benzo[h]quinolines takes place, exclusively. Such highly substituted annelated pyridine systems can be modified in subsequent, selective reactions to build up new N-heterocycles with promising microbiological properties. Antibacterial and antiproliferative assays against four cell mammalian cell lines demonstrate that some of the sulfur-substituted benzo[h]quinolines analogs display potent phenotypic bioactivities in the single-digit micromolar range.

Hypotrochoidal profile contours have been produced in industrial applications in recent years using twin-spindle processes, and they are considered effective high-quality solutions for positive shaft–hub connections. This study mainly concerns analytical approaches to determine the bending stresses in hypotrochoidal profile shafts. The formulation was developed according to bending principles using the mathematical theory of elasticity and conformal mappings. The loading was further used to investigate the rotating bending behaviour. The stress factors for the classical calculation of maximum bending stresses were also determined for all those profiles presented and compiled in the German standard DIN3689-1 for practical applications. The results were also compared with the corresponding numerical and experimental results, and very good agreement was observed. Additionally, based on previous work, the stress factor was determined for the case of torsional loading to calculate the maximum torsional stresses in the standardised profiles, and the results are listed in a table. This study contributes to the further refinement of the current DIN3689 standard.

Cervical cancer is one of the ailments that endangers the health of women all over the world and causes infertility. Fortunately, this disease can be avoided. Both the results and participation rates of the current preventative strategy remain poor. Hence, preventative or early detection methods remain challenging and open. In gynecology and computer science fields, few studies on identifying cervical cancer are based on behavior risk factor and machine learning. Moreover, various social and behavioral aspects might often make it more difficult to detect cervical cancer especially in low‑ and middle‑income countries (LMICs). Accordingly, focus on predicting the presence of cervical cancer through behavioral risk factors is the basic structure of this research. We proposed an approach to classify cervical cancer from a social-behavioral perspective using logistic regression to predict cervical cancer. We got significantly improved outcomes than the existing methods. Moreover, we used feature engineering to formulate less dimensionality as a pre-processing step and optimized parameters to be prepared for classification phase. The results proved that using the logistic regression with regularization type L1 had a promising performance. The accuracy of Logistic Regression (LR) L1 was 97.2%. Such results support the proposed work as a reliable classification predictive tool.

Due to the digitization and Internet of Things revolutions, the present electronic world has a wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a growing concern in today's cyber security industry all over the world. Traditional security solutions are insufficient to address contemporary security issues due to the rapid proliferation of many sorts of cyber-attacks and threats. Utilizing artificial intelligence knowledge, especially machine learning technology, is essential to providing a dynamically enhanced, automated, and up-to-date security system through analyzing security data. In this paper, we provide an extensive view of machine learning algorithms, emphasizing how they can be employed for intelligent data analysis and automation in cybersecurity through their potential to extract valuable insights from cyber data. We also explore a number of potential real-world use cases where data-driven intelligence, automation, and decision-making enable next-generation cyber protection that is more proactive than traditional approaches. The future prospects of machine learning in cybersecurity are eventually emphasized based on our study, along with relevant research directions. Overall, our goal is to explore not only the current state of machine learning and relevant methodologies but also their applicability for future cybersecurity breakthroughs.

Artificial Intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus AI-based modeling is the key to building automated, intelligent, and smart systems according to today's needs. To solve real-world issues various types of AI such as analytical, functional, interactive, textual, and visual AI can be applied to enhance the intelligence and capabilities of an application. However, developing an effective AI model is a challenging task due to the dynamic nature and variation in real-world problems and data. In this paper, we present a comprehensive view on "AI-based Modeling" with the principles and capabilities of potential AI techniques that can play an important role in developing intelligent and smart systems in various real-world application areas including business, finance, healthcare, agriculture, smart cities, cybersecurity and many more. We also emphasize and highlight the research issues within the scope of our study. Overall, the goal of this paper is to provide a broad overview of AI-based modeling that can be used as a reference guide by academics and industry people as well as decision-makers in various real-world scenarios and application domains.

: Extra- and intra-cellular activity occurs under the direction of numerous inter-molecular interactions, and in any tissue or cell, molecules are densely packed, thus promoting those molecular interactions. Galectins and chemokines, the focus of this review, are small, protein effector molecules that mediate various cellular functions, in particular cell adhesion and migration, as well as cell signaling/activation. In the past, researchers have reported that combinations of these (and other) effector molecules act separately, yet sometimes in concert, but nevertheless physically apart and via their individual cell receptors. This view that each effector molecule functions independently of the other limits our thinking about functional versatility and cooperation, and, in turn, ignores the prospect of physiologically important inter-molecular interactions, especially when both molecules are present or co-expressed in the same cellular environment. This review is focused on such protein-protein interactions with chemokines and galectins, their homo- and hetero-oligomeric structures that they can form, and the functional consequences of those paired interactions.

Due to the rising dependency on digital technology, cybersecurity has emerged as a more prominent field of research and application that typically focuses on securing devices, networks, systems, data and other resources from various cyber-attacks, threats, risks, damages, or unauthorized access. Artificial Intelligence (AI), also referred to as a crucial technology of the current Fourth Industrial Revolution (Industry 4.0 or 4IR), could be the key to intelligently dealing with these cyber issues. Various forms of AI methodologies, such as analytical, functional, interactive, textual as well as visual AI can be employed to get the desired cyber solutions according to their computational capabilities. However, the dynamic nature and complexity of real-world situations and data gathered from various cyber sources make it challenging nowadays to build an effective AI-based security model. Moreover, defending robustly against adversarial attacks is still an open question in the area. In this paper, we provide a comprehensive view on "Cybersecurity Intelligence and Robustness", emphasizing multi-aspects AI-based modeling and adversarial learning that could lead to addressing diverse issues in various cyber applications areas such as detecting malware or intrusions, zero-day attacks, phishing, data breach, cyberbullying and other cybercrimes. Thus the eventual security modeling process could be automated, intelligent, and robust compared to traditional security systems. We also emphasize and draw attention to the future aspects of cybersecurity intelligence and robustness along with the research direction within the context of our study. Overall, our goal is not only to explore AI-based modeling and pertinent methodologies but also to focus on the resulting model's applicability for securing our digital systems and society.

The digital world has a wealth of data, such as Internet of Things (IoT) data, business data, health data, mobile data, urban data, security data, and many more, in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting knowledge or useful insights from these data can be used for smart decision-making in various applications domains. In the area of data science, advanced analytics methods including machine learning modeling can provide actionable insights or deeper knowledge about data, which makes the computing process automatic and smart. In this paper, we present a comprehensive view on "Data Science'' including various types of advanced analytics methods that can be applied to enhance the intelligence and capabilities of an application through smart decision-making in different scenarios. We also discuss and summarize ten potential real-world application domains including business, healthcare, cybersecurity, urban and rural data science, and so on by taking into account data-driven smart computing and decision making. Based on this, we finally highlight the challenges and potential research directions within the scope of our study. Overall, this paper aims to serve as a reference point on data science and advanced analytics to the researchers and decision-makers as well as application developers, particularly from the data-driven solution point of view for real-world problems.

Vehicle windshield wiper system increases the driving safety by contributing a clear shot viewing to the driver. In this paper, modelling, designing and simulation of a vehicle windshield wiper system with robust control theory is done successfully. H∞ loop shaping and robust pole placement controllers are used to improve the wiping speed by tracking a reference speed signals. The reference speed signals used in this paper are step and sine wave signals. Comparison of the H∞ loop shaping and robust pole placement controllers based on the two reference signals is done and convincing results have been obtained. Finally the comparative results prove the effectiveness of the proposed H∞ Loop Shaping controller to improve the wiping mechanism for the given two reference signals.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

Na⁺/H⁺ exchangers (NHEs) are known to be important regulators of pH in multiple intracellular compartments of eukaryotic cells. Sperm function is especially dependent on changes in pH and thus it has been postulated that NHEs play important roles in regulating the intracellular pH of these cells. For example, in order to achieve fertilization, mature sperm must maintain a basal pH in the male reproductive tract and then alkalize in response to specific signals in the female reproductive tract during the capacitation process. Eight NHE isoforms are expressed in mammalian testis/sperm: NHE1, NHE3, NHE5, NHE8, NHA1, NHA2, NHE10, and NHE11. These NHE isoforms are expressed at varying times during spermatogenesis and localize to different subcellular structures in developing and mature sperm where they contribute to multiple aspects of sperm physiology and male fertility including proper sperm development/morphogenesis, motility, capacitation, and the acrosome reaction. Previous work has provided evidence for NHE3, NHE8, NHA1, NHA2, and NHE10 being critical for male fertility in mice and NHE10 has recently been shown to be essential for male fertility in humans. In this article we review what is known about each NHE isoform expressed in mammalian sperm and discuss the physiological significance of each NHE isoform with respect to male fertility.

A simple undirected graph $\Gamma=(V_\Gamma,E_\Gamma)$ admits an $H$-covering if every edge in $E_\Gamma$ belongs to at least one subgraph of $\Gamma$ that isomorphic to a graph $H$. For any graph $\Gamma$ admitting $H$-covering, a total Labelling $\beta: V_\Gamma \cup E_\Gamma \longrightarrow \{1,2,\dots,p\}$ is called an $H$-irregular total $p$-labelling of $\Gamma$ if every two different subgraphs $H_1$ and $H_2$ of $\Gamma$ isomorphic to $H$ have distinct weights where the weight $w_\beta(K)$ of subgraph $K$ of $\Gamma$ is defined as $w_f(K):=\displaystyle \sum_{v\in V_K} f(v) + \sum_{e\in E_K} f(e)$. The smallest number $p$ for which a graph $\Gamma$ admits an $H$-irregular total $p$-labelling is called the total $H$-irregularity strength of $\Gamma$ and is denoted by $ths(\Gamma)$. In this paper, we determine the total $H$-irregularity strength of edge comb product of two graphs.

This article will briefly review the progress of h-BN based solid-state metal semiconductor metal (MSM) neutron detectors. In the last decade, several groups have been working on hexagonal boron nitride (h-BN) based solid-state neutron detectors. Recently, the detection efficiency of 59% has been reported. Efficient, low-cost neutron detectors made from readily available materials are essential for various applications. Neutron detectors are widely used to detect fissile materials and nuclear power plants for security applications. The most common and widely used neutron detectors are 3He based, which are sometimes bulky, difficult to transport, have high absorption length, need relatively high bias voltage (>1000 V), and have low Q-value (0.764 MeV). Also, 3He is not readily available material. Thus, there is a strong need to find an alternative detection material. 10B isotope has a high neutron absorption cross-section, and it has been tested as a coating on the semiconducting materials. Due to the two-step process, neutron capture through 10B, and then electron-hole pair generation in a typical semiconducting material, the efficiency of these devices is not up to the mark. The progress in h-BN based detectors requires a review to envision the further improvement in this technology.

A methodology based on the concepts that arise from Density Functional Theory named Conceptual Density Functional Theory (CDFT) was chosen for the calculation of some global and local reactivity descriptors of the Discodermins A-H family of marine peptides through the consideration of the KID (Koopmans in DFT) technique that was successfully used in previous studies of this kind of molecular systems. The determination of active sites of the studied molecules for different kind of reactivities was achieved by resorting to some CDFT-based descriptors like the Fukui functions as well as the Parr functions derived from Molecular Electron Density Theory (MEDT). A few properties identified with their ability to behave as a drug and the bioactivity of the peptides considered in this examination were acquired by depending on a homology model by studying the correlation with the known bioactivity of related molecules in their interaction with various biological receptors. With the further object of analyzing their bioactivity some parameters of usefulness for future QSAR studies, their predicted biological targets and the the ADME (Absorption, Distribution, Metabolism, and Excretion) parameters related to the Discodermins A-H pharmacokinetics are also reported.

Customs law and procedures are important part of the trade system in Jordan. They regulate the flow of goods across the borders. The purpose of this paper is to examine Jordan's import regime by analyzing customs law, rules of origin, free trade zones, and tariffs reform.

The Jordanian Law of Commercial Agents and Intermediaries No. 28 of 2001 and the Emirati Commercial Agency Law No. 2 of 2010 cover all forms of sale contracts through intermediaries. These Laws provide express restrictions and protective provisions on the conduct by local agents of internal commercial agency activities. However, these statutory protections are granted only to registered agencies conducted by national agents.The Jordanian legislator does not regulate the issue of agency exclusivity, which can constitute a restraint of trade and leads to a state of market monopolization. Courts in Jordan have exclusive jurisdiction in settling disputes arising out of agency agreements. However, this exclusive jurisdiction does not cover unregistered commercial agencies which are treated as enforceable commercial contracts under the general provisions prescribed in the Commercial Code.Under the Jordanian Law the principal cannot terminate the agency agreement at any time, but he can dismiss its renewal upon the expiry of its date without justified grounds. Certain statutory protections provided by the Jordanian laws raise barriers to entry to their national markets. This statutory policy violates the specific commitments made by Jordan with respect to market access and national treatment established by the GATS.

The central nervous system (CNS) is the final frontier in drug delivery because of the blood-brain barrier (BBB), which poses significant barriers to the access of most drugs to their targets. Kynurenic acid (KYNA), a tryptophan (Trp) metabolite, plays an important role in behavioral functions and abnormal KYNA levels have been observed in neuropsychiatric conditions. The current challenge lies in delivering KYNA to the CNS owing to its polar side chain. Recently, C-3 side chain modified KYNA analogs have been shown to cross the BBB; however, it is unclear whether they retain the biological functions of the parent molecule. This study examined the impact of KYNA analogs, specifically SZR-72, SZR-104, and the newly developed SZRG-21, on behavior. The analogs were administered intracerebroventricularly (i.c.v.), and their effects on the motor domain were compared with those of KYNA. Specifically, open field (OF) and rotarod (RR) tests were employed to assess motor activity and skills. SZR-104 increased horizontal exploratory activity in the OF test at a dose of 0.04 μmol/4 μL, while SZR-72 decreased vertical activity at doses of 0.04 and 0.1 μmol/4 μL. In the RR test, however, neither KYNA nor its analogs showed any significant differences in motor skills at either dose. Side chain modification affects affective motor performance and exploratory behavior, as the results show for the first time. In this study, we showed that KYNA analogs alter emotional components such as motor-associated curiosity and emotions. Consequently, drug design necessitates the development of precise strategies to traverse the BBB while paying close attention to modifications in their effects on behavior.

Past public health crises (e.g. tobacco, alcohol, opioids, cholera, HIV, lead, pollution, venereal disease, even COVID-19) have been met with interventions targeted both at the individual and all of society. While the healthcare community is very aware that the global pandemic of non-communicable diseases (NCD’s) has its origins in our Western ultraprocessed food diet, society has been slow to initiate any interventions other than public education, which has been ineffective, in part due to food industry interference. This article provides the rationale for such public health interventions, by compiling the evidence that added sugar, and by proxy the ultraprocessed food category, meets the four criteria set by the public health community as necessary and sufficient for regulation — addiction, toxicity, ubiquity, and externalities (how does your consumption affect me?). To its credit, some countries have recently heeded this science and have instituted sugar taxation policies to help ameliorate NCD’s within their borders. This article also supplies scientific counters to food industry talking points, in order to guide both scientists and policy makers in instituting further appropriate public health measures to quell this pandemic.

Rotavirus species H (RVH) has been detected in pigs, humans and bats. Moreover, porcine RVHs have been recently identified in several swine-producing countries. Despite their zoonotic impact, genome information of RVHs is still limited. This study aimed to establish a tentative complete genome-based genotyping system for RVHs, by appending genomic sequences from 12 porcine RVHs identified in Japan between 2013 and 2015 to those from human and other porcine RVHs reported in previous studies. Phylogenetic analysis of 11 RNA segments indicated that porcine RVHs could be classified into multiple genotypes. Consequently, the genotype classification for RVHs revealed the existence of genotypes 10G, 6P, 6I, 3R, 4C, 7M, 6A, 2N, 4T, 6E, 3H for the genes VP7, VP4, VP6, VP1, VP2, VP3, NSP1, NSP2, NSP3, NSP4 and NSP5, respectively. Surprisingly, two distinctive types in NSP1 and NSP3 genes were identified from among the twelve porcine RVHs. Our data suggest a potentially novel gene rearrangement event between porcine RVH and rotavirus species C in the NSP3 gene. These findings would provide a new insight in understanding for evolution of RV.

In the current age of the Fourth Industrial Revolution ($4IR$ or Industry $4.0$), the digital world has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data, business data, social media data, health data, etc. To intelligently analyze these data and develop the corresponding real-world applications, the knowledge of artificial intelligence (AI), particularly, machine learning (ML) is the key. Various types of machine learning algorithms such as supervised, unsupervised, semi-supervised, and reinforcement learning exist in the area. Besides, the deep learning, which is part of a broader family of machine learning methods, can intelligently analyze the data on a large scale. In this paper, we present a comprehensive view on these machine learning algorithms that can be applied to enhance the intelligence and the capabilities of an application. Thus, this study's key contribution is explaining the principles of different machine learning techniques and their applicability in various real-world applications areas, such as cybersecurity, smart cities, healthcare, business, agriculture, and many more. We also highlight the challenges and potential research directions based on our study. Overall, this paper aims to serve as a reference point for not only the application developers but also the decision-makers and researchers in various real-world application areas, particularly from the technical point of view.

Meningitis is a severe disease associated with death in children under five with highest rates of infections under age of one. Vaccines for Neisseria meningitides and Haemophilus influenza are used to prevent the main causative agents of meningitis. Administration of H. influenzae type b (Hib) vaccine is recommended at 2, 4 and 6 months with a booster dose at 18 months. N. meningitidis has two commercially available vaccines, the pure polysaccharide is recommended at 24 months meanwhile the protein-conjugated vaccines at 12 months. We sought in this study to examine if coadministering the vaccines for the two main meningitis causing bacteria might be synergistic as a preliminary step towards the possibility of shuffling immunization schedule. So, we coadministered Hib vaccine with commercially available vaccines either quadrate (ACWY) polysaccharide meningococcal (Men) or conjugated meningococcal (Nim) vaccines in Balb/C mice (n = 6/group) and compared to each vaccine administered separately and controls. Thirty-five days post immunization, we measured specific antibodies titers. Hib vaccine increased Men antibody titers significantly for serotypes Y and W. When Hib vaccine was coadministrated with Nim, antibody titer for Y, W and A significantly increased. For serotype C, there was no significant difference in antibody titers among immunized groups. As for effect of meningococcal vaccines on Hib, Men significantly increased Hib antibody titers while Nim had no effect. Collectively, our data suggested that coadministration of Hib and Men or Nim vaccines was safe and had synergistic effect on immune responses elicited to both vaccines. Further studies are needed before immunization schedule modifications. Such immunization schedule recommendation should provide better protection against this life-threatening disease in young children.

: Clay covers a substantial portion of the Earth. Such soil covers Iraq’s central and southern regions, where the depth of the clay may reach 150 m. All enhancement techniques and methods for transporting large loads cease to function or become prohibitively expensive in such soils. In this case, thermal treatment is the most effective method. In this study, a novel heating system was created and produced utilizing gas as the heat source via boreholes that simulate reality. The borehole heating cases were planted inside soft clay soil to enhance the soil. Different parameters were investigated, including the spacing between boreholes (3, 4, and 5 times the outer diameter of the borehole), the heating depth (1, 1.5, 2, and 2.5 times the width of the model footing), the duration of heating (2, 4, 6, 8, and 10 hrs), and the pattern (square, circular, triangular). The results showed the strength and behavior of the soil treated with heated boreholes at varying spacings, depths, patterns, and heating periods. The best results were found for a spacing, depth, and heating time of three times the outer diameter of the borehole, two times the width of the footing model, and eight hours, respectively. The effect of the heated borehole casing pattern was small when the heated borehole casing was used. The experiments conducted on heated soil showed that the undrained shear strength (Cu) increased from 14 to 360 kPa and then dropped to 140 kPa (as an average with depth). In contrast, the average angle of internal friction (Ø) rose from 0 to 52 degrees and decreased to 16 degrees (as an average with depth) from the center of the heating model to the furthest point affected by heating. In addition, the EDS pattern showed that components like silicon, aluminum, and iron dropped at 300 °C and rose at 400 °C in the treated soils. At 200 °C, the calcium content rose, and then dropped dramatically at 400 °C. The carbon percentage increased at 300 °C and decreased at 400 °C. The elements’ proportions showed little change or remained stable at temperatures between 400 °C and 600 °C.

The WTO is here to stay. Institutions are never perfect. The way the WTO, as an institution, runs its business may not be perfect either. Arab countries are attempting to broaden their engagement in the multilateral trading system in a manner that has many implications. This engagement includes accession to the WTO, participation in WTO dispute resolution mechanism, and representations at the WTO.

A review of the surface ablation of hominin teeth by attrition, abrasion and erosive wear. The occurrence of these lesions is explored in a sample of South African fossil australopithecine dentitions revealing excessive wear. Interpretation of the nature of the dietary components causing such wear in the absence of carious erosion provides insight into the ecology of the Plio-pleistocene epoch (1-2 million years ago). Fossil teeth inform much of the living past by their retained evidence after death. Tooth wear is the ultimate forensic evidence of lives lived.

Artificial Intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (Industry 4.0), which can be used for the protection of Internet-connected systems from cyber-threats, attacks, damage, or unauthorized access. To intelligently solve today's various cybersecurity issues, popular AI techniques involving Machine Learning (ML) and Deep Learning (DL) methods, the concept of Natural Language Processing (NLP), Knowledge Representation and Reasoning (KRR), as well as the concept of knowledge or rule-based Expert Systems (ES) modeling can be used. Based on these AI methods, in this paper, we present a comprehensive view on "AI-driven Cybersecurity" that can play an important role for intelligent cybersecurity services and management. The security intelligence modeling based on such AI methods can make the cybersecurity computing process automated and intelligent than the conventional security systems. We also highlight several research directions within the scope of our study, which can help researchers do future research in the area. Overall, this paper's ultimate objective is to serve as a reference point and guidelines for cybersecurity researchers as well as industry professionals in the area, especially from an AI-based technical point of view.

.Various synthetic nematicides are currently used effectively in the control of plant parasitic nematodes. However, these nematicides have adverse effects on humans and the environment. Neem oil is eco-friendly alternatives to synthetic nematicides. The effectiveness of repeated neem oil application in suppressing the root-knot nematodes infestation in figs seedlings was therefore examined in this study, both in its natural form (10 ml/L) and in its nano-emulsion form (5 and 7 ml/L). The recorded reduction parameters of M. incognita were J2/250g soil, galls and egg masses / 5g roots of infected fig seedlings were measured at that time, and the effects of these natural additives were compared with the Fosthiazate (Krenkel 75%EC). The impact of such soil amendments on some typical plant parameters, the total microbial count of soil, and the overall enzymatic activity of the fig rhizosphere were also included. Obtained results revealed that the soil population density of root knot nematode suppressed by 80.3% , reduction of nematode egg masses (60.4%) due to the application of nano-emulsion of neem oil (at 7ml/L). Present work recommend the use of nano-emulsion of neem oil as one of the effective and eco-friendly means to reduce the root- knot nematode on fig .

The food additive sorbic acid is considered as an effective preservative for certain cereal products, and propionic acid is commonly added in bakery wares, e.g. bread and fine bakery wares. The aim of this study is to develop and validate a new nuclear magnetic resonance spectroscopy (¹H NMR) method for routine screening and quantification of sorbic and propionic acids in bread and several bakery products for quality control purposes. Results showed that none of the screened samples contained higher concentrations than regulatory maximum limits. However, for some samples, labelling of preservatives was lacking or they were used in food categories, for which the use is not approved. It can be concluded that the developed NMR method can be used for routine screening of bakery products.

Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is nowadays considered as a core technology of today's Fourth Industrial Revolution (4IR or Industry 4.0). Due to its learning capabilities from data, DL technology originated from artificial neural network (ANN), has become a hot topic in the context of computing, and is widely applied in various application areas like healthcare, visual recognition, cybersecurity, and many more. However, building an appropriate DL model is a challenging task, due to the dynamic nature and variations in real-world problems and data. Moreover, the lack of core understanding turns DL methods into black-box machines that hamper development at the standard level. This article presents a structured and comprehensive view on DL techniques including a taxonomy considering various types of real-world tasks like supervised or unsupervised. In our taxonomy, we take into account deep networks for supervised or discriminative learning, unsupervised or generative learning as well as hybrid learning and relevant others. We also summarize real-world application areas where deep learning techniques can be used. Finally, we point out ten potential aspects for future generation DL modeling with research directions. Overall, this article aims to draw a big picture on DL modeling that can be used as a reference guide for both academia and industry professionals.

Deep learning (DL), which is originated from an artificial neural network (ANN), is one of the major technologies of today's smart cybersecurity systems or policies to function in an intelligent manner. Popular deep learning techniques, such as Multi-layer Perceptron (MLP), Convolutional Neural Network (CNN or ConvNet), Recurrent Neural Network (RNN) or Long Short-Term Memory (LSTM), Self-organizing Map (SOM), Auto-Encoder (AE), Restricted Boltzmann Machine (RBM), Deep Belief Networks (DBN), Generative Adversarial Network (GAN), Deep Transfer Learning (DTL or Deep TL), Deep Reinforcement Learning (DRL or Deep RL), or their ensembles and hybrid approaches can be used to intelligently tackle the diverse cybersecurity issues. In this paper, we aim to present a comprehensive overview from the perspective of these neural networks and deep learning techniques according to today's diverse needs. We also discuss the applicability of these techniques in various cybersecurity tasks such as intrusion detection, identification of malware or botnets, phishing, predicting cyber-attacks, e.g. denial of service (DoS), fraud detection or cyber-anomalies, etc. Finally, we highlight several research issues and future directions within the scope of our study in the field. Overall, the ultimate goal of this paper is to serve as a reference point and guidelines for the academia and professionals in the cyber industries, especially from the deep learning point of view.

In August 4 2011, United Nations Environmental Program (UNEP) submitted an unprecedented, scientific, groundbreaking Environmental Assessment Report (EAR) of Ogoniland, to the Nigerian government. This was the outcome of a 14–month intensive evaluation of the extent of pollution. It was intended that UNEP’s recommendations would be implemented to restore the devastated environment, on the one hand, and on the other, counteract the numerous environmental health issues that have for decades, plagued Ogoniland. However, five years post EAR, and, despite the seriousness of the situation, no significant resolution has occurred, both on the part of the government, and on the part of Shell Petroleum Development Company (SPDC) or Shell. To date, millions of Niger Delta residents, particularly those living in the oil-bearing communities, continue to suffer severe consequences. Although, the assessment was conducted in Ogoniland, other communities in the Niger Delta are also affected. This article explores prevailing issues, using Ogoniland (a microcosm of the Niger Delta) as an example. A multidisciplinary approach for sustainable mitigation of environmental health risks in the Niger Delta is paramount, and Environmental Management tools offer valuable strategies. Adopting UNEP’s recommendations for addressing environmental health problems requires implementing the Environmental Management/Environmental Management System (EM/EMS) model.

Antioxidant activity is an essential feature required for oxygen-sensitive merchandise and goods, such as food and corresponding packaging as well as materials used in cosmetics and biomedicine. For example, vanillin, one of the most prominent antioxidants, is fabricated from lignin, the second most abundant natural polymer in the world. Antioxidant potential is primarily related to the termination of oxidation propagation reactions through hydrogen transfer. The application of technical lignin as a natural antioxidant has not yet been implemented in the industrial sector, mainly due to the complex heterogeneous structure and polydispersity of lignin. Thus, current research focuses on various isolation and purification strategies to improve the compatibility of lignin material with substrates and enhancing its stabilizing effect. This contribution presents antioxidant capacity studies of various lignins depending on purification degree of the raw material. In detail, the antioxidant potential of lignin-based compounds is studied using the DPPH (2,2-diphenyl-1-picrylhydrazyl) assay. The purification procedure was monitored by thin layer chromatography (TLC) and showed that double-fold selective extraction is the most efficient purification procedure (confirmed by UV-Vis, FTIR, HSQC and 31P NMR spectroscopy, SEC and XRD analysis). Results are discussed regarding the dependency of antioxidant activity on lignin structure and biomass source. Thus, lignins obtained from industrial black liquor are compared with beech wood samples. In addition, the influence of lignin isolation (kraft versus organosolv) is discussed. Values of the antioxidant activity (DPPH inhibition) of kraft lignin fractions were 62-68% while beech and spruce/pine-mixed lignins showed values between 26, 64 and 42%, respectively. TPC values of the different isolated kraft lignin fractions varied between 26-35%, while beech, spruce/pine lignins were 34, 30 and 34%, respectively. Storage decreased the TPC values and increased the DPPH inhibition.

This brief commentary challenges the use of the term "energy deficiency" in nutrition and metabolism, providing a critical examination of its scientific and philosophical aspects. It emphasizes the need to consider rare diseases associated with actual energy deficiency, which extend beyond the scope of everyday tiredness or fatigue. By analyzing energy balance and its complexities, this critique underscores the oversimplification associated with the term and its potential for misleading implications. It highlights the dynamic nature of energy metabolism and the intricate mechanisms involved in maintaining energy equilibrium, including the impact of rare genetic and physiological abnormalities. In addition to the discussion on energy balance, this commentary explores the manifestation of rare diseases that disrupt energy production, utilization, or hormonal regulation. Conditions such as mitochondrial diseases, glycogen storage diseases, adrenal insufficiency, and Prader-Willi syndrome are examined, shedding light on their profound impact on individuals' energy levels and overall health. The distinct time courses, underlying mechanisms, and clinical implications of protein deficiency, energy deficiency, and vitamin C deficiency are also compared, further emphasizing the complexity of energy metabolism and its relationship with various nutrient deficiencies. To foster a more comprehensive understanding of energy metabolism and enhance clarity in communication within the field, the commentary proposes the adoption of alternative terminology, such as "energy flux," to capture the multifaceted nature of energy balance more accurately. By reevaluating the terminology employed, researchers and healthcare professionals can better convey the intricate dynamics of energy metabolism and address the unique challenges faced by individuals with rare diseases causing actual energy deficiency. In conclusion, this commentary serves as a thought-provoking exploration of the concept of energy deficiency in nutrition and metabolism. It highlights the limitations of the term in capturing the complexities of energy balance, particularly in the context of rare diseases. By broadening the discussion to include these rare conditions, it encourages a more comprehensive understanding of energy metabolism and calls for precise and nuanced terminology to facilitate effective communication and advancements in the field.

The present work reports on the calculated electronic and magnetic structure of the binary Co-Ga system at high Co content. β-CoGa adopts a simple cubic CsCl type structure. Well-ordered CoGa does not exhibit collective magnetism but is a paramagnetic, metallic compound. Neither Co nor Ga deficiency induces magnetic order, however, ferromagnetism is observed for Co-Ga anti-site disorder. The magnetic moment per cell increases up to about 1.2 μB in the completely disordered body centered cubic structure. With increasing Co content, Co1+xGa1−x maintains the CsCl type structure and becomes ferromagnetic. Most important, a discontinuity of the magnetic order with composition is observed at about 10% excess Co, where a change from a low magnetic moment state to a high moment state is observed. This is accompanied by a change in the electronic structure and transport properties. The discontinuity is forced by the increasing exchange splitting related to the localized moment of the additional Co atoms that replace Ga. Subsequently, the magnetic moment increases continuously up to 2.5 μB for x=0.6. For x≳0.6, the structure changes to face centered cubic with random site occupation and the magnetic moment further increases. Above the magnetic discontinuity, the Curie temperature increases linearly with the Co content from the onset of ferromagnetism, until it reaches its maximum in pure Co.

We can improve our knowledge of the factors influencing women's decisions to have a caesarean section rather than a vaginal delivery, slow the rise in the caesarean section rate, encourage mothers to have vaginal delivery, and provide practical solutions to health system planners through statistical analysis of the proportion of women who prefer caesarean sections. This investigation is cross-sectional. It involved gathering information from 60 women (20–42 years old) who had given birth via caesarean section over four months, beginning in October 2022 and ending in January 2023. The main reasons of a caesarean section were presence of a fibrous node (caused by previous caesarean sections that were repeated) at 16.67%, intrauterine foetal death at 15%, cervical stenosis at 8.33% , 8.33% of births were repeated due to obstructed labour; 6.66% of caesareans were carried out because the mother contracted or had her uterus removed in order to prevent having children. This study found that there were a lot of complications. The bleeding or anaemia cases accounted for the highest percentage of complications (20%), followed by high blood pressure (16.67%), high fever (10%), and either shortness of breath, blood clotting, urinary tract infection, or wound inflammation (10%). The results of the current study indicated that the level of education, the employment of mothers, and the age of the pregnant were the most important social and demographic factors for increasing the rate of caesarean sections

This study aims to identify modern bureaucratic government phenomenon expressed in W.H. Auden’s poem “The Unknown Citizen” (UC). This phenomenon will be revealed through the use of figures of speech, symbols and imagery in the poem. This poem is chosen as the object of the study since phenomenon happened in the poem represents people’s life and government practice in the modern era. Government, in the poem, seems to be very dominant. Its bureaucratic apparatus is powerful. Through its sophisticated technology, the bureau of statistics is able to detect the citizen’s identity. But, ironically, it could have not identified UC’s name as he lived in the world. He, then, was honored by the state by being erected the marble monument. The poem is analyzed by applying phenomenological criticism. The analysis finds that the representation of modern government is expressed through symbols emphasized by dramatic irony and supported by the use of internal sensation imagery. UC is the allegory of the average person with his bravery he sacrifices for the country. The state ought to give him an honor. In this poem Auden, actually, wants to write a parody for establishing monuments in some countries to honor the struggles of their soldiers who died in the World War I. Those monuments are really tombs since the function of a monument is a state’s thanksgiving for their sacrifice.

Entamoeba histolytica, like other Organismes, is characterized by diversity and heterogeneity in its genetic content, which is one of the most important reasons for survival, and the increase in susceptibility to infection.Non-condensation of chromosomes during the process of cell division and the ambiguity of the chromosomal ploidy makes predicting the exact chromosomal number difficult. Genes distributed across 14 chromosomes as well as many extra-chromosome elements. Most Genes composed of one axon only, with Introns in 25% of Genes. This genome is characterized by the presence of Polymorphic internal repeat regions, and several gene families, one of these large families encoding Transmembrane kinas, Cysteine protease (CP), SREHP protein, and others.

As a renewable industrial crop, Miscanthus offers numerous advantages, namely high photosynthesis activity (as a C4 plant) and exceptional CO2 fixation rate. These properties make Miscanthus very attractive for industrial exploitation, such as lignin generation. Here, we present a systematic study analyzing the correlation of the lignin structure with Miscanthus genotype and plant portion (stem versus leaf). Specifically, the ratio of the three monolignols and corresponding building blocks as well as the linkages formed between the units have been studied. Depending on the Miscanthus genotype and plant component (leaf versus stem), correlations between chemical structure and properties of the lignins have been determined, i.e. correlations in molecular weight, polydispersity and decomposition temperature. Lignin isolation was performed using non-catalyzed organosolv pulping and the structure analysis includes NREL, FTIR, UV-Vis, HSQC-NMR, TGA, pyrolysis GC/MS. Structural differences were found for stem and leaf-derived lignins. Compared to beech wood lignins, Miscanthus lignins possess lower molecular weight and narrow polydispersities (< 1.5 Miscanthus vs. > 2.5 beech) corresponding to improved homogeneity. In addition to conventional univariate analysis of FTIR spectra, multivariate chemometrics revealed distinct differences for aromatic in-plane deformations of stem versus leaf-derived lignins. These results emphasize the potential of Miscanthus as low-input resource and Miscanthus-derived lignin as promising agricultural feedstock.

This paper applies conceptualization from Paulo Freire, Tracey Nicholls, and bell hooks to develop a framework to understand art- and media-based communication of knowledge. Increasing use of art and digital media in research and formal educational settings emphasize knowledge-communication intent, and the theory attempts to rationalize why individuals potentially devalue, discard, or misconstrue messaging. Drawing upon two case studies: children’s literature, and existing scholarship on true crime as a media genre, the framework proposes art and media consumption based on perceived task-applicability of art and media. Stemming from the complex nature of socially-imposed, self-determined, and art- & media-instated tasks that an individual may face throughout their lifetime, an individual may be drawn to Freirean power and privilege - even fictional depictions - as societal structures can grant power and privilege with universal task-applicability. Potential usage of this framework towards participatory, qualitative inquiries conclude the paper, in attempt to support future art and media designed with knowledge-communication intent.

Lamin A, B and C, the nuclear intermediate-filament proteins, play a role in epigenetic regulation. While Lamin B is expressed in all nucleated cells studied, Lamin A/C are transcribed in most somatic cell types except mature B lymphocytes. Since Epstein-Barr virus (EBV), a human gammaherpesvirus, is associated with tumorigenic processes and is known to alter the epigenotype of its host cells, we studied the expression of the LMNA gene and its epigenetic marks in EBV-carrying human lymphoid cell lines. We observed a high lamin A/C mRNA and protein expression in EBV-immortalized lymphoblastoid cell lines (LCLs) and in group III Burkitt lymphoma (BL) lines where hypomethylated first exons were observed with activating histone marks. In most cell lines with low promoter activity a highly methylated first exon could be detected. Our data showed that methylation of the first exon of LMNA was associated with the downregulation of LMNA expression whereas euchromatic histone marks were enriched at active LMNA promoters in EBV-immortalized LCLs. These data suggest a role for viral latency products to activate LMNAp in EBV-infected latency type III B cells in vitro. Expression of lamin A/C may contribute to the establishment of activated B cell phenotype that needs further explorations.

Corporate governance is developing rapidly in many countries across the world. In this article, the existing state of corporate governance in Jordan is examined. Jordan does not have a corporate governance code per se. The article reveals that overall Jordan has in place some of the features of corporate governance best practice, but that there remains further progress to be made in areas such as independence of directors, compensation, and correlation between shareholding and entitlement to seats on the board. The article recommends legal reforms in order to enhance corporate governance in Jordan.

RAxML-NG is a new phylogentic inference tool that replaces the widely-used RAxML and ExaMLtree inference codes. Compared to its predecessors, RAxML-NG offers improvements in accur-acy, flexibility, speed, scalability, and user-friendliness. In this chapter, we provide practicalrecommendations for the most common use cases of RAxML-NG: tree inference, branch supportestimation via non-parametric bootstrapping, and parameter optimization on a fixed tree topo-logy. We also describe best practices for achieving optimal performance with RAxML-NG, inparticular, with respect to parallel tree inferences on computer clusters and supercomputers. AsRAxML-NG is continuously updated, the most up-to-date version of the tutorial described inthis chapter is available online at: https://cme.h-its.org/exelixis/raxml-ng/tutorial .

We present a modification of the logistic model of epidemics that takes into account the possibility that an epidemic can develop from multiple physically-distinct hot spots with a range of starting times. This produces an improved understanding of the time evolution of the COVID-19 epidemic taking place in the United States in the spring of 2020.

In situations of uncertainty, scenarios serve as input for evidence-based decision making. However, past experience shows that not all scenarios are treated equally, and we hypothise that only those based ion a world view shared by decision makers are perceived as credible and receive full attention. While intuitively plausible, this hypothesis has not been analysed by quantitative correlation analyses, so instead of drawing on quantitative data the paper analyses the archetypical scenarios developed in the ALARM project to substantiate the plausibility by a comparative analysis of world views, value systems and policy orientations. Shock scenarios are identified as a means to explore the possibility space of future developments beyond the linear developments models and most scenario storylines suggest. The analysis shows that the typical scenarios are based on mutually exclusive assumptions. In conclusion, a comparison of storyline and empirical data can reveal misperceptions, policy failures and the need to rethink world views as a necessary step to open up to new challenges. Deeply held beliefs will make this a transition unlikely to happen without severs crises, if not dedicated efforts to reveal the role of world views for scenarios and policies are undertaken.

Nowadays, there has been a significant rise in the consumption of kefir, a functional beverage touted for its perceived health benefits. To offer a high-quality beverage to consumers, it is imper-ative to scrutinize and fine-tune the fermentation process. This study seeks to investigate the im-pact of fermentation time and the number of subcultures on the physicochemical, microbiological, and volatile composition, as well as the visual appearance of kefir beverages obtained from four consecutive 24- or 48-h batch subcultures. All fermented beverages exhibited low lactose, ethanol and acids levels, with counts of viable probiotic lactic acid bacteria and yeast exceeding 106 colony forming units/mL. The four kefir beverages from the 48-h batch subcultures notably showed the lowest total concentrations of volatile compounds likely due to overfermentation and overacidifi-cation of the beverages. This caused separation of the whey and curd, along with the formation of large gas bubbles, negatively affecting the visual appearance of the products. These findings em-phasize the importance of fine-tuning the fermentation process to ensure the production of high-quality kefir beverages that align with consumer preferences. The four beverages from the 24-h batch subcultures exhibited high microbiological and physicochemical stability during stor-age at 4 °C for 28 days.

Higher salt (sodium) intake has been associated with a higher blood pressure (BP). The association degree may be influenced by factors such as age, origin and dietary components. This study aimed to evaluate the 24-hours urinary sodium (Na) and potassium (K) excretion in normotensive and hypertensive Dominicans adults and estimate their salt intake. 163 volunteers (18-45, 46-80 years) participated in a cross-sectional study. 24-hours Na and K urinary excretion were measured using an ion selective electrode technique. Na and K urinary excretion (99.4±46.5 and 35.0±17.5 mmol/24h) did not correlated with BP, except in the normotensive group in which K correlated with SBP (0.249, p=0.019). Na and K excretion were similar for normo- and hypertensive subjects. Na-to-K molar ratio (3.1±1.3) was higher in younger subjects (p=0.040). Na-to-K ratio was associated with DBP in the total group (r=0.153, p=0.052), in the hypertensive group (r=0.395, p<0.001) and in the older group with SBP (0.350, p=0.002) and DBP (0.373, p<0.001). In the older group, Na-to-K ratio and DBP correlated after controlling for subjects with hypertension controlled by treatment (r=0.236, p=0.041). The Na-to-K ratio correlated, when salt intake was over 5g/d (52.2%), with SBP (rho=0.219, p=0.044) and DBP (rho=0.259, p=0.017). Determinants of BP were age-dependent and in younger subjects were: sex (SBP, beta: 14.02±2.87, p<0.001) and body mass index (BMI) (beta:-12.07±3.72, p=0.001, beta:9.44±2.87, p=0.001, for SBP and DBP, respectively) and, in the olders, the Na-to-K ratio, for SBP (beta:6.7±2.4, p=0.005) and DBP (beta:3.8±1.1, p<0.001). The mean Na and salt intakes (2.3 and 5.8 g/d) were slightly higher and K intake lower (1.4 g/d) than WHO recommendations.

Incretin effect helps in regulating glucose homeostasis and maintaining glycaemic control within the human body. This effect is achieved by the two naturally occurring incretin hormones: glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1). Such hormones released by specialized entero-endocrine cells of the gastrointestinal tract cause insulin augmentation after food consumption. However, incretin effects are impaired in type 2 diabetic, primarily attributed to the deterioration of GLP-1 function along with decreased GLP-1 receptor expression. Targeting this hormone has, therefore, become an important therapeutic approach to treat this diabetic condition. Native GLP-1’s brief half-life and rapid proteolytic degradation have generated significant enthusiasm in uncovering the long-acting GLP-1 receptor (GLP-1R) agonists to manage type 2 diabetes. These synthetic peptides mimic the natural GLP-1 to activate GLP-1R and effectively exert various physiological benefits in terms of weight management, blood pressure, lipid profile, obesity and major adverse cardiovascular event. This review paper provides insights into the structure, function and expression of GLP-1 and its receptor. It also summarizes existing literature regarding different types of GLP-1 receptor agonists, their effects on blood pressure and how they exert their actions. While animal models have contributed significantly to this area of study, the scarcity of human studies is noted, indicating a need for more investigation in this domain. Expanding research in humans will help in comprehending the impact of GLP-1 receptor agonists on blood pressure regulation and their underlying mechanisms.

The precise determination of the State-of-Health (SOH) of lithium-ion batteries is critical in the domain of battery management systems. The proposed model in this research paper emulates any deep learning or machine learning model by utilizing a Look Up Table (LUT) memory to store all activation inputs and their corresponding outputs. The operation that follows the completion of training is referred to as the LUT memory preparation procedure. The lookup operation performed on this method simply substitutes for the inference process. This is achieved by discretizing the input data and features before binarizing them. The term for the aforementioned operation is the LUT inference method. The procedure was evaluated in this study using two distinct neural network architectures: a bidirectional long short-term memory (LSTM) architecture and a standard fully connected neural network (FCNN). It is anticipated that considerably greater efficiency and velocity will be achieved during the inference procedure when the pre-trained deep neural network architecture is inferred directly. The principal aim of this research is to construct a lookup table that effectively establishes correlations between the SOH of lithium-ion batteries and ensures a degree of imprecision that is tolerable. According to the results obtained from the NASA PCoE lithium-ion battery dataset, the proposed methodology exhibits performance that is largely comparable to that of the initial machine learning models. Utilising the error assessment metrics RMSE, MAE, and (MAPE), the accuracy of SOH prediction has been quantitatively evaluated. The indicators mentioned above demonstrate a significant degree of accuracy when predicting SOH.

In the design of multi-loop Networked Control Systems (NCSs) wherein each control system is characterized by heterogeneous dynamics and associated with certain set of timing specifications and constraints, appropriate metrics need to be employed for the synthesis of control and networking policies to efficiently respond to the requirements of each control loop. Majority of the design approaches for sampling, scheduling and control policies include either time-based or event-based metrics to perform pertinent actions in response to the changes of the parameters of interest. We specifically focus in this article on Age-of-Information (AoI) as a recently-developed time-based metric and threshold-based triggering function as a generic event-based metric. As the NCS model, we consider multiple heterogeneous stochastic linear control systems that close their feedback loops over a shared-resource communication network. We investigate the co-design across the NCS, and discuss the pros and cons with AoI and ET approaches in terms of asymptotic control performance measured by linear-quadratic Gaussian (LQG) cost functions. In particular, sampling and scheduling policies combining AoI and stochastic event-triggered metrics are proposed. It is argued that pure AoI functions that generate decision variables solely upon minimizing the average age irrespective of control systems dynamics may not be able to improve the overall NCS performance even compared with pure randomized policies. Our theoretical analyses are successfully validated through several simulation scenarios.

H-adaptivity is an effective tool to introduce local mesh refinement in FEM-based numerical simulation of crack propagation. The implementation of h-adaptivity could benefit the numerical simulation of fatigue or accidental load scenarios involving large structures such as ship hulls. In engineering applications, the element deletion method is frequently used to represent cracks. However, the element deletion method has some drawbacks such as strong mesh dependency and loss of mass or energy. In order to mitigate this problem, the element splitting method could be applied. In this study, a numerical method called ‘h-adaptive element splitting’ (h-AES) is introduced. The h-AES method is applied in FEM programs by combining h-adaptivity with the element splitting method. Two examples using the h-AES method to simulate cracks in large structures under linear-elastic fracture mechanics scenario are presented. The numerical results are verified against analytical solutions. Based on the examples, the h-AES method is proven to be able to introduce mesh refinement in large-scale numerical models that consist of structured coarse meshes. By employing the mesh refinement introduced in this paper, very small cracks are well represented in large structures.

Many spectroscopic diagnostics are routinely used as a technique to infer the plasma parameters from line emission spectra but their accuracy depends on the numerical model or code used for the fitting process. However, the validation of a line shape code requires some steps : comparison of the line shape code with other similar codes for some academic (simple) cases and then more complex ones, comparison of the fitting parameters obtained from the best fit of the experimental spectra with those obtained with other diagnostic techniques and/or comparison of the fitting parameters obtained by different codes to fit the same experimental data. Here we compare the profiles of the hydrogen Balmer β line in a helium plasma computed by six codes for a selected set of plasma parameters and we report on the plasma parameters inferred by each of them from the fitting to a number of experimental spectra measured in a helium corona discharge where the pressure was in the range 1- 5 bar.