The most common form of mixed dementia (MixD) is constituted by abnormal protein deposits associated with Alzheimer´s disease (AD) that coexist with vascular disease. Although olfactory dysfunction is considered a clinical sign of AD-related de-mentias, little is known about the impact of this sensorial impairment in MixD at molecular level. To address this gap in knowledge, we have assessed olfactory bulb (OB) proteome-wide expression in MixD subjects (n=6) respect to neurologically intact controls (n=7). Around 9% of the quantified proteins were differentially expressed, pinpointing aberrant proteostasis involved in synaptic transmission, nucleoside monophosphate and carbohydrate metabolisms and neuron projection regeneration. In addition, net-work-driven proteomics revealed a modulation in cell-survival related pathways such as ERK, AKT and PDK1-PKC axis. Part of the differential OB protein set was not specific of MixD, being also deregulated across different tauopathies, synucleinopathies and tardopathies. However, the comparative functional analysis of OB proteome data between MixD and pure AD pathologies deciphered commonalities and differences between both related phenotypes. Finally, olfactory proteomics allowed to propose serum Prolow-density lipoprotein receptor-related protein 1 (LRP1) as a candidate marker to differentiate AD from MixD phe-notypes.

We present an overview over eight brightly luminescent Cu(I) dimers of the type Cu2X2(PN)3 with X = Cl, Br, I and P^N = 2-diphenylphosphino-pyridine (Ph2Ppy), 2-diphenylphosphino-pyrimidine (Ph2Ppym), 1-diphenylphosphino-isoquinoline (Ph2Piqn) including three new crystal structures (Cu2Br2(Ph2Ppy)3, 1-Br, Cu2I2(Ph2Ppym)3, 2-I, and Cu2I2(Ph2Piqn)3, 3-I). However, we mainly focus on their photo-luminescence properties. All compounds exhibit combined thermally activated delayed fluorescence (TADF) and phosphorescence at ambient temperature. Emission color, decay time, and quantum yield varies over large ranges. For deeper characterization, we select Cu2I2(Ph2Ppy)3, 1-I, showing a quantum yield of 81 %. DFT and SOC-TDDFT calculations provide insight into the electronic structures of the singlet S1 and triplet T1 states. Both stem from metal+iodide-to-ligand charge transfer transitions. Evaluation of the emission decay dynamics, measured from 1.2 ≤ T ≤ 300 K, gives ∆E(S1-T1) = 380 cm-1 (47 meV), a transition rate of k(S1→S0) = 2.25×106 s-1 (445 ns), T1 zero-field splittings, transition rates from the triplet substates, and spin-lattice relaxation times. We also discuss the interplay of S1-TADF and T1-phosphorescence. The combined emission paths shorten the overall decay time. For OLED applications, utilization of both singlet and triplet harvesting can be highly favorable for improvement of the device performance.

Guava is a vital fruit worldwide, especially in Pakistan, and due to its nutritional value famous in each age group. Due to a very short shelf life, the marketing and export of this fruit faced severe constraints. Therefore, in the current study, edible coating of chitosan (0, 0.5, 1.0, 1.5, and 2.0%) was evaluated on postharvest shelf life when guava fruits were stored (room temperature and 4 °C temperatures) for 12 days. The chitosan treated coating fruits have shown reduced total sugars and malondialdehyde levels compared to untreated control samples. However, a significant difference (p ≤ 0.05) in total sugar and malondialdehyde levels exists between samples stored in m compared to refrigerated temperature (4 °C). The chitosan-coated samples have shown a greater amount of vitamin C, quercetin, rutin, and total phenolic contents than control samples. However, these nutritional parameters' levels were significantly different (p ≤ 0.05) in samples stored at room than samples stored at refrigerated temperature. However, the levels of crude fiber, potassium, and sodium were found statistically nonsignificant (p ≥0.05) in control versus chitosan treated coating treatments. The findings have documented that the coatings of 1.5 and 2.0% were most effective for extension in shelf life and maintaining the nutritional attributes of guava fruit.

In this research, a model is presented to detect and monitor the rotor bar’s condition of large motors. This proposed model uses two diagnostic methods MCSA and ZCT, to extract the fault components. The input of the proposed model is only the motor current at two levels of 80% and 100% of the nominal motor load, which by using the two methods MCSA and ZCT and making changes in how to use them can be the disadvantages of other methods such as incorrect detection of rotor bars in Large motors with variable load, the harmonical stator voltage (or the presence of the drives) and asymmetric conditions. The extracted components are classified using neural network, instead of experimental and human resources constraints. Using this classification algorithm is high accuracy and the ability to implement in conventional processors. The proposed model has been trained andtested using currents of real large motor data and 96.87% accuracy using neural network to detect faults and monitor the online status of the rotor bars. On the other hand, the proposed model has been implemented in the industrial environment (FiroozkoohCement Factory) and has been able to correctly determine the rotor bars of 4 large suspicious motors announced by the factory technicians.

The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, statistics and data (e.g., local monitoring of Sustainable Development Goals - SDGs) are hindered by the unavailability of spatial data at metropolitan, city and sub-city scales. Deprivation is a complex and multidimensional concept, which has been captured in existing literature with a strong focus on household-level deprivation while giving limited attention to area-level deprivation. Within this scoping review, we build on existing literature on household- as well as area-level deprivation frameworks to arrive at a combined understanding of how urban deprivation is defined with a focus on LMIC cities. The scoping review was enriched with local stakeholder workshops in LMIC cities to arrive at our framework of Domains of Deprivations, splitting deprivation into three different scales and nine domains. (1) Socio-Economic Status and (2) Housing Domains (Household scale); (3) Social Hazards & Assets, (4) Physical Hazards & Assets, (5) Unplanned Urbanization and (6) Contamination (Within Area scale); and (7) Infrastructure, (8) Facilities & Services and (9) city Governance (Area Connect scale). The Domains of Deprivation framework provides a clear guidance for collecting data on various aspects of deprivation, while providing the flexibility to decide at city level which indicators are most relevant to explain individual domains. The framework provides a conceptual and operational base for the Integrated Deprived Area Mapping System (IDEAMAPS) Project for the creation of a data ecosystem, which facilitates the production of routine, accurate maps of deprived “slum” areas at scale across cities in LMICs. The Domains of Deprivation Framework is designed to support diverse health, poverty, and development initiatives globally to characterize and address deprivation in LMIC cities.

We aimed to assess awareness, knowledge, and attitudes of healthy pregnant women towards human papillomavirus (HPV), to estimate factors associated with a positive attitude towards HPV immunization and to assess the uptake of the vaccine among their children. A cross-sectional study was conducted at the University Clinic of Gynecology and Obstetrics, Belgrade, Serbia among pregnant women attending their regular gynecological check-ups at the 12th gestational week. Knowledge about HPV and HPV vaccine was assessed using a specifically designed 12-item and 5-item questionnaires. Out of total 265 included women, 79.3% had heard of HPV, and 37.5% knew that HPV vaccine exists. HPV vaccine knowledge score was associated with higher odds for a positive attitude towards vaccination of both female (OR = 4.10, 95% CI 1.50-11.29) and male (OR = 3.71, 95% CI 1.52-9.01) child. The number of children (OR = 1.32, 95% CI 1.04-1.67) and high vaccine knowledge score (OR = 1.64 95% CI 1.13-2.39) were independent predictors associated with willingness to vaccinate child against HPV. The gynecologist was the preferable point of reference for information seeking about the HPV vaccine. Despite relatively high HPV awareness and knowledge among pregnant women in Serbia, about one-third of them are HPV vaccine aware, and are willing to vaccinate their children against HPV.

The purpose is to verify trends of scientific production from 2010 to 2020, considering the best universities of the United States, China, the European Union (EU) and private companies. The top 30 universities in 2020 in China, the EU, and the US and private companies were selected from the SCImago institutions ranking (SIR). The positions in 2020, 2015, 2010 in SIR and three sub-indicators were analyzed by means of non-parametric statistics, taking into consideration the effect of time and group on rankings. American and European Union universities have lost positions to Chinese universities and even more to private companies, which have improved. In 2020, private companies have surpassed all other groups considering Innovation as sub-indicator. The loss of leadership of European and partly American universities mainly concerns research linked to the production of patents. This can lead to future risks of monopoly that may elude public control and cause a possible loss of importance of research not linked to innovation.

Faba bean (Vicia faba L) is the first grain legume in terms of hectarage, total production and foreign exchange earnings in Ethiopia. The current study was designed to evaluate effect of NPS and bio-organic fertilizers on the yield and yield components of faba bean in Debre Markos University research farm. A total of 16 treatments were made from the factorial combination of four levels NPS (0, 50, 100 and 150 kg ha-1) and four levels bio-organic fertilizer (Nil BOF (Bio(Nil)), rhizobium (Bio(IR)), 10 t ha-1 FYM (Bio(FYM)) and FYM+Rhizobium (Bio(FYM+IR))) in randomized complete block design (RCBD) with three replications. The Walki (EH 96049-2) variety, which is high yielding, moderate disease resistant and water-logging tolerant used as test crop. The result experiment showed that, plot treated with Bio(FYM+IR)+NPS100 treatment gave statically maximum effective number of tillers (2.73), maximum number of pods per plant (20.30), hundred seeds weight (76.11g), grain yield (5.62 t ha-1), biomass yield (10.94 t ha-1) and Harvest index (59.91%) than over other treatments received NPS fertilizer with and without bio-organic fertilizers. Therefore, the combined use of 100kg ha-1 NPS with 10 tha-1 FYM and rhizobium inoculation is superior for optimum production of faba bean in study area.

This research assesses the changes in the total water storage (TWS) during the twentieth century and their future projections in the Nile River Basin (NRB) via TWSA (TWS anomalies) records from GRACE (Gravity Recovery and Climate Experiment), GRACE-FO (Follow-On), data-driven-reanalysis TWSA and land surface model (LSM), in association with precipitation, temperature records, and standard drought indicators. The analytical approach incorporates the development of 100+ yearlong TWSA records using a probabilistic conditional distribution fitting approach by the GAMLSS (Generalized Additive Model for Location, Scale, and Shape) model. The drought and flooding severity, duration, magnitude, frequencies, and recurrence were assessed during the studied period. The results showed, 1- The NRB between 2002 to 2020 has transited to substantial wetter conditions. 2- The TWSA reanalysis records between 1901 to 2002 revealed that the NRB had experienced a positive increase in TWS during the wet and dry seasons. 3- The projected TWSA between 2021 to 2050 indicated slight positive changes in TWSA during the rainy seasons. The analysis of drought and flooding frequencies between 1901 to 2050 indicated the NRB has ~64 dry-years compared to ~86 wet-years. The 100+ yearlong TWSA records assured that the NRB transited to wetter conditions relative to few dry spells. These TWSA trajectories call for further water resources planning in the region especially during flood seasons. This research contributes to the ongoing efforts to improve the TWSA assessment and its associated dynamics for transboundary river basins. It also demonstrates how an extended TWSA record provides unique insights for water resources management in the NRB and similar regions.

Mental health and emotional responses to the effects of COVID-19 lockdown in sub-Saharan Africa (SSA) are of serious public health concern and may negatively affect the mental health status of people. Hence, this study assessed the prevalence of mental health symptoms as well as emotional reactions among sub-Saharan Africans (SSAs) and associated factors among SSAs during the COVID-19 lockdown period. This was a web-based cross-sectional, a study on mental health and emotional features from 2005 respondents in seven SSA countries. This study was conducted between April 27 and May 17, 2020 corresponding to the lockdown period in most SSA countries. Respondents aged 18 years and above and the self-reported symptoms were feeling anxious, being worried, angry, bored and frustrated. These were the main outcomes and were treated as dichotomous variables. Univariate and multivariate logistic regression analyses were used to identify the factors associated with these symptoms. We found that over half (52.2%) of the participants reported any of the mental health symptoms in SSA and the prevalence of feeling bored was 70.5% followed by feeling anxious (59.1%), being worried (57.5%), frustrated (51.5%) and angry (22.3%) during the COVID-19 pandemic. Multivariate analysis revealed that males, those aged >28 years, Central and Southern Africans, those who were not married, the unemployed, those living with more than six persons in a household, had higher odds of mental health and emotional symptoms. Similarly, people who perceived low risk of contracting the infection, and those who thought the pandemic would not continue after the lockdown had higher odds of mental health and emotional symptoms. Health care workers had lower odds for feeling angry than non-healthcare workers. During COVID-19 lockdown periods in SSA, about one in two participants reported mental health and emotional symptoms. Public health measures can be effectively used to identify target groups for prevention and treatment of mental health and emotional symptoms. Such interventions should be an integral component of SSA governments’ response and recovery strategies of any future pandemic.

Antibiotic resistance (ABR) is an emerging global threat to public health. Substantial evidence has indicated that community pharmacists (CPs) can play a critical role in managing the ever-increasing threat of antibiotic resistance. The study aimed to determine the knowledge, attitude, and practices of CPs (n=180) towards antibiotics and antibiotic resistance as well as to improve the rational use of antibiotics. Two phases of mixed methods (quantitative and qualitative) online study were conducted in Pakistan from August 2019 to March 2020 by using validated questionnaires and semi-structured interview data. Different statistical methods were used to tabulate the quantitative data whereas inductive thematic analysis was conducted to categorize themes from the qualitative data and draw conclusions. Approximately 64.4% were male (mean: 29-33 years old). Overall, CPs had good knowledge of and were familiar with superbugs and their roles in ABR (65.6%, Median=1, IQR=1) although they were poor in differentiating some antibiotic groups with their respective ABR patterns (31.1%, Median=1, IQR=1). Most CPs have a positive attitude towards antibiotics with most (90.0%) having identified ABR as a critical issue in public health (Median=1, IQR=0). Overall, CPs' practices towards antibiotics were reasonable where they tend to educate patients about the rational use of antibiotics (52.8%, Median=1, IQR=1). Two main themes (antibiotics and counseling of patients) were related to self-medication with while educational interventions are the sub-theme. ABR is multifactorial where the subthemes related to budget, time constraints incompetent staff, the absence of CPs, the lack of training, enforcement of laws and regulations are the need of the hour in Pakistan. Effective antibiotic stewardship programs, patient education, and awareness campaigns about antibiotics and ABR along with training of the CPs are important factors that have to be addressed in a timely manner.

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory interactions, which study at the global scale has been challenged by the lack of data integration. Here, we update the manually-curated C. glutamicum transcriptional regulatory network, now including protein-protein interactions having a direct effect on gene transcription. The network model with regulations supported by any experimental evidence increased by 557 interactions regarding the previous (2018) version. 73 interactions supported by directed experiments were also included in a second model. We included 545 sRNA-mediated regulations in a third model with a total of 5164 interactions. We deposited the three network models in Abasy Atlas v2.4. We study the C. glutamicum regulatory structure by comparing it against the networks for more than 40 species, finding it to contrast in several global structural properties. We analyze the system-level components of the networks, finding that the inclusion of the sRNAs regulations changes their proportions, transferring part of the basal machinery to the modular class and increasing the number of modules while decreasing their size. Finally, we use strong networks of three model organisms to provide insights in future directions of the C. glutamicum network characterization.

Aiming at the problem that the performance of Adaptive Kalman filter estimation will be affected when the statistical characteristics of the process and measurement noise matrix are inaccurate and time-varying in the linear Gaussian state-space model, an algorithm of Multi-fading factor and update monitoring strategy adaptive Kalman filter based variational Bayesian is proposed. Inverse Wishart distribution is selected as the measurement noise model, the system state vector and measurement noise covariance matrix are estimated with the variational Bayesian method. The process noise covariance matrix is estimated by the maximum a posteriori principle, and the update monitoring strategy with adjustment factors is used to maintain the positive semi-definite of the updated matrix. The above optimal estimation results are introduced as time-varying parameters into the multiple fading factors to improve the estimation accuracy of the one-step state predicted covariance matrix. The application of the proposed algorithm in target tracking is simulated. The results show that compared with the current filters, the proposed filtering algorithm has better accuracy and convergence performance, and realizes the simultaneous estimation of inaccurate time-varying process and measurement noise covariance matrices.

Objectives: To determine the effects of caffeine consumption on the sleep habits and lifestyle of medical students. Methods: A cross-sectional study was conducted at Jinnah Sindh Medical University (JSMU) and Hamdard College of Medicine. On 422 undergraduate students aged 18-25 years, through random sampling. The duration of the study was from January 2019 to June 2019. The data was collected through self-administered questionnaire which included data regarding sleep habits and lifestyle of medical students. Results: Majority (81.6%) of the students consumed caffeine while only (18.4%) did not. One third of the participants (31.8%) reported caffeine consumption increased their academic performance and (57.3%) reported that it does not. More than half of the participants (63.3%) who consumed caffeine slept during class, whereas (47.2%) never had difficulty in falling asleep during the night. Conclusion: This research concluded that caffeine does have some role on sleep habits of medical students as they tend to have less sleep hours, experience day time dysfunction, average quality of sleep, and falling asleep during class. It has been concluded that caffeine has no effect on eating habits of medical students however, it does increase the screening time, keeping them active.

Of the roughly 20,000 canonical human protein sequences, as of September 15, 2020, 6,937 proteins have had their full or partial, medium- to high-resolution structures determined by x-ray crystallography or other methods. Which of these proteins dominate the Protein Data Bank (the PDB) and why? In this paper, we list the 273 top human protein structures based on the number of their PDB entries. This set of proteins accounts for more than 40% of all available human PDB entries and represent past trends as well as current status for protein structural biology. We briefly discuss the relationship which some of the prominent protein structures have with protein research as a whole and mention their relevance to human diseases. The top-10 soluble and membrane proteins are all well-known (most of their first structures being deposited more than 30 years ago). Overall, there is no dramatic change in recent trends in the PDB. Remarkably, the number of structure depositions has grown nearly exponentially over the last 10 or more years (with a doubling time of 7 yrs for proteins from all organisms). Growth in human protein structures is slightly faster (at 5.9 yrs, while E.Coli and Mouse+Rat protein structures accumulate more slowly, Zebrafish protein structures are growing most, at a doubling every 3.7 years, albeit starting from only approx. 100 structure entries in 2010). The information may be informative to senior scientists but also inspire researchers who are new to protein science, providing the year 2020 snap-shot for the state of protein structural biology.

Nowadays, we can observe a worldwide trend towards the development of synthetic biomaterials. Numerous researches have been carried out in order to better understand the cellular behavior involved in the inflammation and bone healing processes related to living tissues. The aim of this study is to evaluate the tissue behavior of two different types of biomaterials: synthetic nano-hydroxyapatite / beta-tricalcium phosphate and hydroxyapatite in non-critical bone defects in rat calvaria. Twenty four rats underwent surgery in which two 3 mm defects in each cavity were performed. The rats were divided into 2 groups: Group 1, using xenogen hydroxyapatite (Bio oss ™); Group 2, using synthetic nano-hydroxyapatite / beta-tricalcium phosphate (Blue Bone ™). Sixty days after the surgery, the calvaria bone defect was filled with biomaterial, the animals were sacrificed and marked with Masson's trichrome and PAS staining, and immunohistochemistry (TNF-α, MMP-9) and electron microscopy analyzes were performed. Histomorphometric analysis indicates a greater presence in the protein matrix in Group 2, in addition to higher levels of TNF-α, MMP-9. The ultrastructural analysis shows an association of material with fibroblasts in the tissue regeneration stage. Paired statistical data indicates that Blue Bone ™ can improve bone formation / remodeling when compared to biomaterials of xenogenous origin.

The science‐policy interface in climate change adaptation became better managed over the past decades. However, the scientists and other knowledge producers, as well as policy makers still need to take bolder steps to more effectively engage with others to apply science and shape up policies. This paper aims to provide practical recommendations, intended to promote conversations between science and policy sectors to address climate change issues. Here, I used two different approaches to synthesize experiences and identify recommendations: a literature review and a case study. The paper stress main findings: (1) The linear communication model is still commonly involved in the science - policy dialogue and proved to be useful to increase the relevance of science and data products to decision makers. (2) When a gap between knowledge producer and knowledge user or decision maker exists, the need for a third party to specialize in bridging the gap become essential. (3) Indigenous people and knowledge must be involved in adaptation policy making based on legitimation local and traditional knowledge, designing the consultation process to broadly engage local and indigenous people, facilitating meaningful dialogues between traditional knowledge and science, and developing initiatives to strengthen skills and capacity of indigenous communities.

We show that low quality of all 427 Brazilian SARS-CoV-2 genomes recently published in Science (1) challenges their phylogenetic inference and may lead to incorrect typing of viral strains in clades with no statistical support. Absence of basecalling quality in genome assemblies and proper phylogeny parameter estimates preclude the assessment of signal-to-noise ratio in the data, downstream analysis and conclusions.

Managing epidemics need to unite each individual of the nations. Lockdown is an essential strategy to fatal and threatening epidemic. All of the citizens should realize that each of people has a responsibility to support the public health crisis. How to organize individual to fight against the epidemic plaque depends each of them. This essay discussed the COVID-19 pandemic relevant self-governance of community from a historical perspective in China. Self-governance of neighborhood committee and community residential office in urban and rural helped to control the COVID-19 pandemic in the communities in China. Co-operation and collective responsibility of citizens and community support is a critical condition to prevent epidemic. The community self-governance can track back Qin Dynasty in China history. It established baojia system to maintain social control for thousand years. Now, the community-based system, baojia system is becoming more autonomous for local citizenship and socialized governance in China. We reviewed a historical pneumonia plaque in North China in 1911. Chinese doctor, Wu Lien-teh (伍連德) confronted the epidemic crisis with many measures such as lockdown, quarantine, the wearing of mask, setup mobile hospitals, travel restriction, the cremation of victims, and border control. Dr. Wu made effort to establish the modern public health service in China. We think that the combination of culture background of China community with modern public healthcare system determinedly played important role to control the COVID-19 pandemic.

Introduction: The COVID-19 pandemic is a global crisis, the number of cases and deaths are on a steep incline. This article reviews the possible immunological mechanisms which underlie the disease pathogenesis by looking at the behaviour of previous coronaviruses not only in humans but also other mammals which possibly act as reservoir hosts. Observations: A key aspect of this coronavirus as well as the previous SARS CoV seems to be the importance of host immune response in the pathology and clinical severity of illness caused by them. A hyperactive innate immune state in combination with an exhausted adaptive immune response are possible determinants of severe illness. Conclusion: There is a possibility that the current SARS CoV 2 has immune evasive tactics similar to SARS CoV in its repertoire, since they share a 76% homology. These might have been learnt behaviour from long periods of persistence in their reservoir hosts and they may be the reason behind the dysregulated immune response evoked in humans. That in turn is highly likely to be one of the factors which govern disease severity. With this in mind we want to bring the medical community’s attention to a ‘hit early, hit hard’ intervention as a possible strategy to modify the course of the disease and bring down the numbers of severe sufferers.

There is now evidence that, based on cytokine profiles, bipolar disorder (BD) is accompanied by simultaneous activation of the immune-inflammatory response system (IRS) and the compensatory immune-regulatory system (CIRS), and that both components may be associated with the staging of illness. Nevertheless, no BD studies have evaluated the IRS/CIRS ratio using CD (cluster of differentiation) molecules expressed by peripheral blood activated T effector (Teff) and T regulatory (Treg) subpopulations. This study examined T cell subsets both before and after ex vivo anti CD3/CD28 stimulation using flow cytometric immunophenotyping in 25 euthymic BD patients and 21 healthy controls as well as human cytomegalovirus (HCMV)-specific IgG antibodies. BD is associated with a significantly lowered frequency of baseline (unstimulated) CD3+CD8+CD71+ and CD4+CD25+FOXP3 and increased CD4+CD25+FOXP3+CD152+ frequencies and with lowered stimulated frequencies of CD3+CD8+CD71+, CD4+CD25+FOXP3+CD152+ and CD4+CD25+FOXP3+GARP cells and, consequently, by an increased stimulated Teff/Treg ratio. Moreover, the number of manic, but not hypomanic or depressive episodes, is significantly and negatively associated with the stimulated proportions of CD3+CD4+CD154+, and CD69+ and CD71+ expression on CD4+ and CD8+ cells, while duration of illness (≥ 10 years) is accompanied by a depleted frequency of stimulated CD152+ Treg, and CD154+ and CD71+ CD4+ T cells. BD and anti-human cytomegalovirus (HCMV) IgG levels significantly interact to decrease the expression of CD4+CD25+FOXP+GARP T phenotypes. In conclusion, BD is characterized by deficits in immune-regulatory functions while the staging of illness is characterized by additional impairments is Teff and Treg activation. HCMV seropositivity may contribute to an immune-risk phenotype associated with BD.

Aims: The lack of information about the inter variability of the test results obtained by CLSI and EUCAST requires further clarifications to interpret antimicrobial susceptibility patterns better. This study aimed to compare the CLSI and EUCAST interpretations of the antimicrobial susceptibility test results of the ESBL–producing uropathogenic Escherichia coli and Klebsiella pneumonia strains. Methods: After obtaining 157 ESBL-producing E. coli and 95, ESBL-producing K. pneumonia isolates from the urine specimens of the patients, Kirby-Bauer’s disc diffusion method was used for conducting antimicrobial susceptibility test. The test procedures and the interpretation of the results were carried out according to the year 2017 versions of both of the two guidelines. For the statistical comparison of concordance between the two guidelines, the Kappa coefficients and the concordance rates were calculated. Results: The results were graded in the range from perfect to poor agreement. For E. coli, interpretations of the AST results revealed a moderate to perfect agreement between both methods. Weighted Kappa agreement scores in the range from 0.42 to 1. The agreement for AMC, TPZ30/6, ceftazidime 10, meropenem, and aztreonam was poor without any inconsistencies. For Klebsiella, the kappa agreement score was in the range from 0.25 to 1. It was incompatible with AMC, TPZ 30/6, ceftazidime 10, aztreonam; there was poor agreement for cefepime, amikacin and ertapenem. Conclusions: Our results showed agreement between the two guidelines for uropathogenic extended-spectrum ß-lactamase producing Escherichia coli and Klebsiella pneumoniae but also showed inconsistencies between two guidelines. Therefore, the results of our study contribute to the comparison of these guidelines for interpreting antibiotic susceptibilities.

This study was conducted to investigate the impact of El Niño Southern Oscillation on rainfall distribution and productivity of major Agricultural crops in the Kembta Tembaro Zone of Southern Ethiopia over the past 30 years. Precipitation and temperature data were obtained from the National Meteorology Agency, crop data from the Central Statistical Agency of Ethiopia, and the Sea Surface Temperature data from the NOAA website. The rainfall trend had shown decreasing trend with high variability at all the stations (p<0.05). Over the same period, El Niño and La Niña event were observed and highly affected rainfall distribution. It was found that Coefficient Variation was greater than 30%, which indicates the area was prone to drought episodes. The impacts of the ENSO events on the yield of Maize, Wheat, Barely, Sorghum and Enset were assessed. Wheat and Maize were highly affected by the ENSO events. Enset was found to be more resistant crop to the influence of ENSO. Barely and Sorghum were affected at varying magnitude. Among the five chosen crop for this investigation two of the crops were seriously affected during the two extremes, i.e. El Niño and La Niña. From this investigation it is conclude that the overall cereal crop productivity was decreased and precipitation variability was noticed. So, having the information about ENSO phase in advance can be used to forecast ENSO and select crop types and varieties to maximize agricultural rain fed cereal crop productivity while minimizing the crop risk associated with seasonal rainfall and ENSO phases.

Introduction: Patients’ satisfaction was extensively researched over the last decades, given its role in building loyalty, compliance to treatment, prevention, and eventually higher levels of wellbeing and improved health status. Patients’ feedback on the perceived quality of health services can be incorporated into practice; therefore, understanding factors and mechanisms responsible for patients’ satisfaction allows providers to tailor targeted interventions. Method: A questionnaire assessing patients’ perception of the quality of health services was administered to a country-representative sample of 1500 Romanian patients. Using a partial least squares—path modeling approach (PLS-PM), with cross-sectional data, we developed a variance-based structural model, emphasizing the mediating role of trust and satisfaction with various categories of health services. Results: We confirmed the mediating role of trust in shaping the relationship between the procedural accuracy of health professionals, along with the perceived intensity of their interaction with patients, and patients’ experienced quality of the health services. We confirmed the mediating role of satisfaction by the categories of services in the relationship between waiting time on the premises, attention received, and the perceived reliability of the information received, as predictors, and the experienced quality of the health services. In addition, indirect assessment of patients’ satisfaction is a good predictor for direct assessment, thereby affirming the idea that the results of the two types of evaluations converge. Discussions: One of the most efficient solutions to increase both patients’ satisfaction and their compliance is to empower the communication dimension between patients and health practitioners. Given the non-linear relationships among variables, we advocate that, unless the nature of the relationships between satisfaction and its predictors is understood, practical interventions could fail. The most relevant variable for intervention is the degree of attention patients perceive they received. We suggest three methods to turn waiting time into attention given to patients.

The relationship between Climate Change and Water is an obvious and key issue within the Sustainable Development Goals. This study aims to investigate the social representation created around this relationship in three different territorial contexts in order to evaluate the influence of the territory on the perception of the risk of Climate Change and its relationship with water. By means of a questionnaire completed by 1709 university students, the climatic literacy of the individual was evaluated in order to relate it to other dimensions on the relationship between Climate Change and Water (information, training previous on climate change and pro-environmental attitudes) in their different dimensions in three different territorial contexts. The results show that the socio-cultural context influences the social representation of Climate Change, but not from the climatological condition, so that it is reasonable to think that the social representation of this relationship is favoured by a common culture around this relationship.

Nowadays, mindfulness-based interventions (MBI) have experimented a remarkable development of studies among childhood and adolescent interventions. For this reason, dispositional mindfulness (DM) measures for children and adolescents have been developed to determine the effectiveness of MBI at this age stage. However, little is known about how key elements of DM (f. e., cognitive de/fusion or experiential avoidance that both conform psychological inflexibility) are involved in the mechanisms of the children and adolescents’ mental health outcomes. This research examined the mediating effect of cognitive fusion between DM and anxiety and other negative emotional states in a sample of 318 Spanish primary-school students (aged between 8 and 16 years, M=11.24, SD=2.19, 50.8% males). Participants completed the AFQ-Y, which is a measure of psychological inflexibility that encompasses cognitive defusion and experiential avoidance; CAMM (DM for children and adolescents), PANAS-N (positive and negative affect measure for children, the Spanish version of PANASC), and STAIC (an anxiety measure for children). The study accomplished ethical standards. As MBI relevant literature has suggested, cognitive defusion was a significant mediator between DM and symptoms of both negative emotions and anxiety in children and adolescents. However, experiential avoidance did not show any significant mediating relationship. Probably, it is needed improvement of the assessment of experiential avoidance. MBI programs for children and adolescents may include more activities for reducing the effects of the cognitive defusion on their emotional distress.

Although work events can be regarded as pivotal elements of organizational life, only a few studies have examined how positive and negative events relate to and combine to affect work engagement over time. Theory suggests that to better understand how current events affect work engagement (WE), we have to account for recent events that have preceded these current events. We present competing theoretical views on how recent and current work events may affect employees (e.g., getting used to a high frequency of negative events or becoming more sensitive to negative events). Although the occurrence of events implies discrete changes in the experience of work, prior research has not considered whether work events actually accumulate to sustained mid-term changes in WE. To address these gaps in the literature, we conducted a week-level longitudinal study across a period of 15 consecutive weeks among 135 employees, which yielded 849 weekly observations. While positive events were associated with higher levels of WE within the same week, negative events were not. Our results support neither satiation nor sensitization processes. However, high frequencies of negative events in the preceding week amplified the beneficial effects of positive events on WE in the current week. Growth curve analyses show that the benefits of positive events accumulate to sustain high levels of WE. WE dissipates in the absence of continuous experience of positive events. Our study adds a temporal component and informs research that has taken a feature-oriented perspective on the dynamic interplay of job demands and resources.

Introduction: studies in the last two decades have found declining snake populations in both temperate and tropical sites, including informal reports from Drake Bay, Costa Rica. Objective: to investigate if reports of decreasing snake populations in Drake Bay had a real basis, and if environmental factors, particularly temperature, rain and light, have played a role in that decrease. Methods: we worked at Drake Bay from 2012 through 2017 and made over 4000 h of transect counts. Using head flashlights we surveyed a transect covered by lowland tropical rainforest at an altitude of 12–38 m above sea level, near the Agujas River, mostly at 1930–2200 hours. We counted all the snakes that we could see along the transect. Results: snake counts increase from August to September and then decline rapidly. The May snakes/rainfall peaks coincide, but the second snake peak occurs one month before the rain peak; we counted more snakes in dry nights, with the exception of Imantodes cenchoa which was equally common despite rain conditions. We saw less Leptodeira septentrionalis on bright nights, but all other species were unaffected. Along the six years, the number of species with each diet type remained relatively constant, but the number of individuals declined sharply for those that feed on amphibians and reptiles. We report Rhadinella godmani, a highland species, at 12–38 m of altitude. Conclusion: night field counts of snakes in Drake Bay, Costa Rica, show a strong decline from 2012 through 2017.

Rett syndrome (RTT) is mainly caused by mutations in methyl CpG-binding protein 2, cyclin-dependent kinase-like 5, or forkhead box protein G1. These RTT-causing proteins harbor an intrinsically disordered region (IDR) whose conformation exhibits spatiotemporal heterogeneity, which not only confer versatility to the protein, but also implicates them in diseases. The IDR generally evolves more rapidly than an ordered structure. In this study, we examined the relationship between pathogenic RTT-associated point mutations in RTT-causing proteins and the evolutionary dynamics of sequence features including structural order–disorder, phosphorylation sites, and evolutionary rates. We also analyzed the molecular properties and evolution of proteins that interact with RTT-causing proteins in terms of phylogenetic profiles, tissue specificity, subcellular localization, expression level, and functions. The results indicate that constrained IDRs may function by forming contacts with other regions in the protein sequence causing pathogenic missense mutations likely to arise in the rapidly evolving IDR and affect molecular networks, leading to disease. The results also provide novel insights into the genetic basis for RTT and the evolution of the neocortex in higher vertebrates.

Literature pertaining to youth development has identified the importance of understanding the physical, intellectual and emotional needs of adolescent youth. The purpose of this study was to compare the use of a ‘traditional’ and ‘progressive’ coaching style to train a general male youth population to improve sprint and jump performances, whilst assessing enjoyment to comment on long term application. Maximal sprint times, sprint kinematics, unilateral jump distances and repetitive tuck jump scores were measured alongside anthropometric variables to characterise performance. Results revealed significant (p>0.05) pre/post differences in anthropometric variables across all maturation groups, and each of the maturational levels displayed a tendency to favour a particular coaching or control condition. Pre-PHV groups responded most effectively to the progressive style of coaching, displaying improvements in horizontal jump performances, and -0.7 to -2.7% improvements in all sprint times, despite also showing the largest increase in tuck jump scores (25.8%). The circa-PHV group produced their greatest improvements in the traditional intervention, as displayed through significant improvements (p<0.05) in 20m sprint times and dominant-leg horizontal jump performance, whilst also revealing the greatest deterioration in tuck jump scores (14.2%). Post-PHV displayed the greatest improvements in the control setting, suggesting the natural benefits gained through adolescent development were greater than the influence of the training interventions. In conclusion, it is suggested that matching coaching strategies and delivery techniques to the period of biological maturation may have implications for both performance and athlete safety.

Scarcity of water is one of the most serious concerns in plant biology with diverse implications at all the levels of molecular, biochemical, and physiological phenomena of plant growth, development, and consequently the productivity. Most of the strategies to induce or enhance drought tolerance in plants are unreasonably expensive and/or time-consuming. Some studies conducted in the recent past have shown that plant growth regulators (PGRs) may induce/improve physiological tolerance in plants to cope with adverse environmental conditions including drought. The present study was aimed at investigating the effects of foliar spray of GABA (0, 1, 2, and 4 mM) applied 20 days following the germination of seeds, on vegetative growth, morphological characteristics, integrity of cell-membrane, and the levels of photosynthetic pigments and enzymatic antioxidants in carrot cvs. Supertaj and Bharat, grown under 100% and 50% field capacity of soil moisture. The treated and untreated (control) carrot plants were harvested and analyzed 2 weeks following the GABA application. The results revealed that foliar application of GABA improved the vegetative growth and significantly increased the levels of free amino acids, plastid pigments, enzymatic antioxidants, and the relative water content in the root crop grown under 50% field capacity of soil moisture, compared to control. Additionally, the GABA application decreased the electrolyte leakage of ions and melondialdehyde (MDA) content in carrot leaves. The carrots harvested from GABA-treated or untreated (control) plants were not significantly different for their protein contents. In conclusion, the incorporation of GABA in the production management of carrots may help plants to mitigate the adverse effects of water deficit stress.

Integrating triple bottom line (TBL) goals into supply chains (SCs) is a challenging task which necessitates the careful coordination of numerous stakeholders’ individual interests. Recent technological advancements can impact TBL sustainability by changing the design, structure and management of modern SCs. Blockchain technology enables immutable data records and facilitates a shared data view along the supply chain. The Physical Internet (PI) is an overarching framework that can be applied to create a layered and comprehensive view of the SC. In this conceptual paper I define and combine these technologies and derive several high-level research areas and research questions to investigate adoption, management as well as structural SC issues. I suggest a theory-based research agenda for the years to come that exploits the strengths of rigorous academic research, while remaining relevant for the industry. Furthermore, I suggest various well-established theories to tackle the respective research questions and provide specific directions for future research.

The application of multiple criteria decision-making (MCDM) techniques in real-life problems has increased in recent years. The need to build advanced decision models with higher capabilities that can support decision making in a broad spectrum of applications, promotes the integration of MCDM techniques with applicable systems, including artificial intelligence, and Geographic Information Systems (GIS). The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are amongst the most widely adopted MCDM techniques capable of resolving water resources challenges. A critical problem associated with water resource management is dam site selection. This paper presents a comparative analysis of TOPSIS and AHP in the context of decision making using GIS for dam site selection. The comparison was made based on geographic and water quality criteria. A ratio estimation procedure was used to determine the weights of these criteria. Both methods were applied for selection of optimal sites for dams in the Sistan and Baluchestan province, Iran. The results show that the TOPSIS method is better suited to the problem of dam site selection for this case study. Actual locations of dams constructed in the area were used to verify the results of both methods.

To close the nutrient-related yield gaps in maize, balanced nutrition using primary and secondary macronutrients as well as micronutrients is recommended. Multi-nutrient diagnostic field trials were conducted in Guinea Savanna of Nigeria to assess the interactive effects of macronutrients and micronutrients on maize grain yields, nutrient uptake as well as N, P and K use efficiencies. The treatments consisted of a control (zero fertilizer applied), an NPK treatment and 10 other treatments in which macronutrient (Mg, S) and/or micronutrients (B, and Zn) were added to the NPK. The experiment was laid out in Randomized Complete Block Design with 3 replications. Data collected were subjected to mixed model with nutrient management strategy as fixed effects while replication nested in location and interaction between location and nutrient management strategy as random effects. The results revealed significant effects (P < 0.05) of nutrient management strategy on maize yield, nutrient uptake and nutrient use efficiencies of N, P and K. The study revealed that yield advantage over the recommended NPK fertilizer as a result of application macronutrients and micronutrients were highest with Mg in Lere (2.4 t ha⁻¹), S + B + Zn in Faskari (2.8 t ha⁻¹), S + B in Doguwa (1.5 t ha⁻¹) and S + Zn in Toro (2.4 t ha⁻¹). Addition of Mg, S and B significantly increases macronutrient uptakes over the recommended NPK only. Agronomic use efficiency, internal utilization efficiency, apparent recovery efficiency and partial factor productivity were significantly increased with the addition of S, Mg, and B but were not improved with Zn application. It was concluded that nutrient limitations to maize in the Guinea Savanna go beyond N, P and K. This study recommends that S, Mg, and B are needed to improve maize productivity and engender improve the use efficiency of NPK fertilizers.

The Australian dairy sheep industry is small and mostly based on a natural grass grazing system which can limit productivity. The current study tested different plant oil-infused and rumen protected polyunsaturated fats and their interactions with sire breeds to improve lactation traits and body condition score (BCS) of ewes grazing low quality pastures. It was hypothesised that supplementing lactating ewe diets plant-derived polyunsaturated oils will improve milk production and composition without compromising BCS. Sixty ewes (n=10/treatment) in mid-lactation, balanced by sire breed, parity, milk yield, body condition score, and liveweight were supplemented with: 1) control: wheat-based pellets without oil inclusion; wheat-based pellets including 2) canola oil (CO); 3) rice bran oil (RBO); 4) flaxseed oil (FSO), 5); safflower oil (SFO) and 6) rumen protected fat containing eicosapentaenoic acid and docosahexaenoic acid (RPO). Except for the control group, all supplementary diets included the same level of 50 ml/kg DM of oil and all diets were isocaloric and isonitrogenous. Experimental animals were grazed in the same paddock with ad libitum access to pasture, hay and water during the 10-week study. RPO was the most effective diet that enhanced milk, fat and protein yields by approximately 30, 13, and 31% respectively (P<0.0001). Significant increase in milk production was also observed in CO, RBO, and SFO (P<0.0001). Breed significantly influenced animal performance with higher milk yield recorded for crossbred Awassi x East Friesian (AW x EF) (578 g/day) vs purebred Awassi (452 g/day) (P<0.0001). This study provides empirical evidence for the use of rumen-protected and plant-derived oil-infused pellets as supplements under low quality pasture grazing conditions, to improve production performance of purebred Awassi and crossbred AW x EF ewes.

Various environmental challenges, related to oil palm commodity has became a major environmental challenge to oil palm production. The aim and objective of this study is to analyze the actual water footprint of oil palm based on root water uptake under varying crop age and soil type. The research was conducted in Pundu Village, Central Kalimantan. The methodology adopted in carrying out this study consists of various stages which includes observing soil moisture, rainfall, and water table, ETo, root water uptake and oil palm water footprint. The highest rate of water consumption was the 13 years oil palm on spodosol soil type with an average daily rate of 3.73 mm/day. The lowest evapotranspiration was represented by the 7th year oil palm on spodosol with an average rate of 3.07 mm/day. The total water footprint value obtained was between 0.56 – 1.14 m3/kg for a variety of plants with various age and soil types. It can be deduced that the water footprint value of oil palm vary for different crop age and soil types on temporal scale. The study also presented that the source of green water from the first root zone of oil palm deliver the highest contribution for oil palm root water uptake.

Background: Staphylococcus aureus (S. aureus) occasionally threatens the life of the host as a persistent pathogen even though it is normal flora of humans and animals. We characterized drug resistance in S. aureus isolated from animal carcasses and milk samples from the abattoirs and dairy farms in the Eastern Cape Province. Methods: A 1000 meat swab samples and 200 raw milk samples were collected from selected abattoirs and dairy farms in the Eastern Cape Province, South Africa. S. aureus was isolated and positively identified using biochemical tests and confirmed by molecular methods. Antibiotic susceptibility test against 14 different antibiotics was performed against all isolates. Antibiotic resistance genes were also detected. Results: Of the 1200 samples collected, 134 (11.2%) samples were positive for S. aureus. Resistance ranged from 71.6% for penicillin G to 39.2% for tetracycline. Resistance gene (blaZ) was detected in 13 (14.9%), while msrA was found in 31 (52.5%) of S. aureus isolates. Conclusions: The present result shows the potential dissemination of multidrug-resistant S. aureus strains in the dairy farms and abattoirs in the Eastern Cape. Therefore, this implies that the organism may rapidly spread through food and pose serious public health risk

Polyethylene glycol (PEG) is an inert, water soluble polymer, used for decades in pharmaceuticals. Although PEG is considered safe, concerns persist about the potential adverse effects of long-term exposure to PEG-containing therapies, specifically in children, following the introduction of PEGylated recombinant factor products used for the treatment of hemophilia. Given the absence of long-term surveillance data, and to evaluate the potential risk, we estimated PEG exposure in the pediatric population receiving US Food and Drug Administration-approved parenteral therapies with pediatric indications. We used a range of pediatric weights and doses based on prescribing information (PI) or treatment guidelines. PIs and reporting websites were searched for information about adverse events (AEs). For a child weighing 50 kg on the highest prophylactic dose of a FVIII product, the range of total PEG exposure was 40–21,840 mg/year; for FIX products, the range was 13–1342 mg/year; and for other products, the range was 383–26,743 mg/year, primarily as a derivative excipient. No AE patterns attributable to PEG were found for any of these products, including potential renal, neurological, or hepatic AEs. Our analyses suggest the pediatric population has had substantial exposure to PEG for several decades, with no evidence of adverse consequences.

The present study was conducted to investigate the effects of rhizome extract of Dioscorea batatas (Dioscoreae Rhizoma, Chinese Yam) and its bioactive compound, allantoin, on myoblast differentiation and mitochondrial biogenesis in skeletal muscle cells. Yams were extracted in water and the extract was analyzed by HPLC. The expression of C2C12 myotubes differentiation and mitochondrial biogenesis regulators were determined by reverse transcriptase (RT)-PCR or Western blot. The glucose levels and total ATP contents were determined by glucose consumption, glucose uptake and ATP assays, respectively. Treatment with yam extract (1 mg/mL) and allantoin (0.2 and 0.5 mM) significantly increased of MyHC expression compared with non-treated myotubes. Yam extract and allantoin significantly increased the expression of mitochondrial biogenesis regulating proteins, PGC1?, Sirt-1, NRF-1, and TFAM, as well as the phosphorylation of AMPK and ACC in C2C12 myotubes. Furthermore, yam extract and allantoin significantly increased the glucose uptake levels and the ATP contents. Finally, HPLC analysis revealed that the yam extract contained 1.53% of allantoin. Yam extract and allantoin, stimulated myoblast differentiation into myotubes and increased energy production through upregulation of mitochondrial biogenesis regulators. These findings indicate that yam extract and allantoin can help to prevent the skeletal muscle dysfunction through stimulation of energy metabolism.

The aim of this study was to develop, implement, and evaluate a new auxiliary enterprise risk management framework and process to serve as an enabler to the global ISO 31000 risk framework and ISO 31010 processes. This framework has been designed particularly for use within high-risk environments and those characterized by volatility, uncertainty, complexity, and ambiguity (VUCA). This paper proposes a methodology for optimization of structured sharing and grass-roots management of all available risk-sentience information with the assessed potential to develop into an identifiable risk in the future. The author introduces new risk terminology including risk-sentience, risk-sentience information, and risk-sentience management. The process involved the development of the Theory of Risk-Sentience (ToRS), Risk-Sentience Auxiliary Framework (RSAF) and a risk-sentience management process referred to as LUOMEAR (Learning from Uncertainties, Others Mistakes, Experiences and Anecdotal Reporting). Manchester Patient Safety Framework (MaPSaF), SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, and a newly developed Risk-Sentience Fertility Checklist were used to conduct pre and post-trial evaluations. The findings include positive adjustments in safety culture, components of commitment to quality, communication and team-working around safety issues, access to evolving risk-information, and efficient sharing and management of recorded risk-information. Recommendations are made for more extensive application of both the proposed auxiliary risk framework and process within high-risk sectors to further explore its effectiveness and scope.

Butanol extracts from leaves, twigs and fruits of Elaeagnus rhamnoides (L.) A. Nelson (sea buckthorn, SBT) were fractionated into phenolic and non-polar lipid components. Their chemical composition was analyzed using the Thermo Ultimate 3000RS chromatographic system, equipped with a diode array detector, a corona-charged aerosol detector, and coupled with a (Q-TOF) mass spectrometer. Assuming that an effect on natural microbiotaand host epithelial cells needs to be assessed, regardless of the purpose of using SBT formulations in vivo, the MIC/MBC/MFC of the fractions and reference phytocompounds were screened involving 17 species of Gram-positive and Gram-negative bacteria and Candida species. The impact of the fractions (subMIC) on the important in vivo persistence properties of S. aureus and C. albicans strains was evaluated. Tests for adhesion and biofilm formation on an abiotic surface and the surfaces conditioned with fibrinogen, collagen, plasma or artificial saliva showed the inhibitory activity of the fractions. The effects on FITC-labeled staphylococci adhesion to fibroblasts (HFF-1) and epithelial cells (Caco-2), and on fungal morphogenesis, indicated that SBT extracts have high anti-virulence potential. Cytotoxicity tests (MTT-reduction) on the standard fibroblast cell line showed variable biological safety of the fractions depending on their composition and concentration.

The aim of this study was to investigate in-vitro antioxidant properties and in-vivo protective effects of different concentrations of Hypericum triquetrifolium Turra. (HT) seed methanol extracts against acute hepatotoxicity, myelotoxicity and hematotoxicity in rats exposed to overdose of cyclophosphamide (CP). HT seed methanol extracts were tested in view of its in-vitro antioxidant activities as total phenolic contents and DPPH free radical-scavenging activity. To investigate in-vivo protective effects of HT seed methanol extracts on rat tissues; tested animals were divided into nine groups. Three groups only were treated with HT extracts (25, 50 and 100 mg/kg HT) for 6 days. Three groups were pre-treated with the extract of HT (25, 50 and 100 mg/kg HT) for 6 days and on the last day they were injected with single dose of CP (150-mg/kg body weight). Two groups were used as control groups and one group was only treated with CP (150 mg/kg) on the 6th day. The toxic effects of CP and protective effects of HT extracts on the nucleated cells which were produced by bone marrow and serum alanine transaminase (ALT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), oxidative stress index (OSI) levels were investigated biochemically. Additionally, liver tissue samples were examined histopathologically. Our results show that HT seed methanol extract has high total phenolic content and antioxidant activity. Over dose CP administration caused hepatotoxicity, myelotoxicity and hematotoxicity on rat. Whereas, 25, 50 and 100 mg/kg HT plus CP administered groups showed significant protective effects on nucleated cells. And 25, 50, 100 mg/kg HT plus CP treated groups showed an important decrease on serum ALT, ALP, LDH and OSI levels when compared with CP treated group. Our results showed that the administration of different HT doses with high doses of CP significantly reduced hepatotoxicity, myelotoxicity and hematoxicity on rats.

Deck inclination and vertical displacements are among the most important technical parameters to evaluate the health status of a bridge and to verify its bearing capacity. Several methods, both conventional and innovative, are used for structural rotations and displacement monitoring; no one of these does allow, at the same time, precision, automation, static and dynamic monitoring without using high cost instrumentation. The proposed system uses a common laser pointer and image processing. The elastic line inclination is measured by analyzing the single frames of a HD video of the laser beam imprint projected on a flat target. For the image processing, a code was developed in Matlab® that provides instantaneous rotation and displacement of a bridge, charged by a mobile load. An important feature is the synchronization of the load positioning, obtained by a GNSS receiver or by a video. After the calibration procedures, a test was carried out during the movements of a heavy truck maneuvering on a bridge. Data acquisition synchronization allowed to relate the position of the truck on the deck to inclination and displacements. The inclination of elastic line was obtained with a precision of 0.01 mrad. The results demonstrate the suitability of the method for dynamic load tests, control and monitoring of bridges.

Ceria, zirconia and mixed cerium-zirconium mesoporous oxides were synthesized and used as supports for sulfur and gold species. The materials were characterised using selected advanced techniques (ICP-OES, elemental analysis, XPS, XRD, N₂ adsorption and desorption isotherms, UV-vis, ATR-FTIR, TPR-H₂, TG-DTA) which allowed monitoring of the oxidation state of metals (cerium and gold) and the surface properties of the catalysts, in particular the concentration of the components on the surface and in the bulk of materials. The interactions between gold, sulfur and metals from oxides were considered. The goal of this work was studied the changes in the chemical composition of materials and the oxidation states of cerium species after the modification of oxides with sulfur and gold species and the estimation of the influence of these changes on the surface properties. The chemical composition of surface affects the mobility of surface oxygen and the oxidation state of cerium, which can play the role of redox sites (e.g. Ce³⁺/Ce⁴⁺ species), and therefore it strongly influences on the adsorption of hydrogen sulfide and then gold loading. Additionally, gold catalysts modified with sulfur species were tested in the reaction of glycerol oxidation in the liquid phase at basic conditions as the test reaction of the catalytic oxidation of organic pollutants from water.

Evidence shows that weightloss improves insulin sensitivity but few studies have examined the effect of macronutrient composition independently of weight loss on direct measures of insulin sensitivity. We randomised 89 overweight or obese women to either a standard diet (StdD) that was intended to be low in fat and relatively high in carbohydrate (n=42) or to a relatively high protein (up to 30% of energy), relatively high fibre (>30g/day) diet (HPHFib) (n=47) for 10 weeks. Advice regarding strict adherence to energy intake goals was not given. Insulin sensitivity and secretion was assessed by a novel method - the Dynamic Insulin Sensitivity and Secretion Test (DISST). Although there were significant improvements in body composition and most cardiometabolic risk factors on HPHFib, insulin sensitivity was reduced by 19.3% (95% CI: 31.8, 4.5%; p=0.013) in comparison with StdD. We conclude that the reduction in insulin sensitivity after a diet relatively high in both protein and fibre, despite cardiometabolic improvements, suggests insulin sensitivity may reflect metabolic adaptations to dietary composition for maintenance of glucose homeostasis, rather than impaired metabolism.

A simple approach to enable water-management agencies employing free data to achieve the goal of using a single set of predictive equations for water-quality retrievals with satisfactory accuracy is proposed. Multiple regression-derived equations based on surface reflectance, band ratios, and environmental factors as predictor variables for concentrations of Total Suspended Solids (TSS), Total Nitrogen (TN), and Total Phosphorus (TP) were derived using a hybrid forward-selection method that considers Variance Inflation Factor (VIF) in the forward-selection process. Landsat TM, ETM+, and OLI/TIRS images were jointly utilized with environmental factors, such as wind speed and water surface temperature, to derive the single set of equations. The coefficients of determination of the best-fitting resultant equations varied from 0.62 to 0.79. Among all chosen predictor variables, ratio of reflectance of visible red (Band 3 for Landsat TM and ETM+, or Band 4 for Landsat OLI/TIRS) to visible blue (Band 1 for Landsat TM and ETM+, or Band 2 for Landsat OLI/TIRS) has a strong influence on the predictive power for TSS retrieval. Environmental factors including wind speed, remote sensing-derived water surface temperature, solar altitude, and time difference (in days) between the image acquisition and water sampling were found important in water-quality parameter estimation.

The aim of this study is to evaluate three different strategies to improve classification accuracy in a highly fragmented semiarid area. i) Using different classification algorithms: Maximum Likelihood, Random Forest, Support Vector Machines and Sequential Maximum a Posteriori, with parameter optimisation in the second and third cases; ii) using different feature sets: spectral features, spectral and textural features, and spectral, textural and terrain features; and iii) using different image-sets: winter, spring, summer, autumn, winter+summer, winter+ spring+summer; and a four seasons combination. A 3-way ANOVA is used to discern which of these approaches and their interactions significantly increases accuracy. Tukey-Kramer contrast using a heteroscedasticity-consistent estimation of the kappa covariances matrix was used to check for significant differences in accuracy. The experiment was carried out with Landsat TM, ETM, and OLI images corresponding to the period 2000-2015. A combination of four images was the best way to improve accuracy. Maximum Likelihood, Random Forest and Support Vector Machines do not significantly increase accuracy when textural information is added, but do so when terrain features are taken into account. On the other hand, Sequential Maximum a Posteriori increases accuracy when textural features are used, but reduces accuracy substantially when terrain features are included. Random Forest using the three feature subsets and Sequential Maximum a Posteriori with spectral and textural features had the largest kappa values, around 0.9.

Background: Appendicular skeletal muscle (or lean) mass (ALM) estimated using dual-energy X-ray absorptiometry (DXA) is considered to be a preferred method for sarcopenia studies. However, DXA is expensive, has limited portability, and requires radiation exposure. Bioelectrical impedance analysis (BIA) is inexpensive, easy to use, and portable; thus BIA might be useful in sarcopenia investigations. However, a large variety of models have been commercially supplied by different companies, and for most consumer products, the equations estimating ALM are not disclosed. It is therefore difficult to use these equations for research purposes. In particular, the BIA equation is often age-dependent, which leads to fundamental difficulty in examining age-related ALM loss. The aims of the current study were as follows: (1) to develop and validate an equation to estimate ALM using multi-frequency BIA (MF-BIA) based on theoretical models, and (2) to establish sarcopenia cutoff values using the equation for the Japanese population. Methods: We measured height (Ht), weight, and ALM obtained using DXA and a standing-posture 8-electrode MF-BIA (5, 50, 250 kHz) in 756 Japanese individuals aged 18 to 86-years-old (222 men and 301 women as developing equation group and 97 men and 136 women as a cross validation group). The traditional impedance index (Ht²/Z₅₀) and impedance ratio of high and low frequency (Z₂₅₀/Z₅) of hand to foot values were calculated. Multiple regression analyses were conducted with ALM as dependent variable in men and women separately. Results: We created the following equations: ALM = (0.6947 × (Ht²/Z₅₀)) + (−55.24 × (Z₂₅₀/Z₅)) + (−10,940 × (1/Z₅₀)) + 51.33 for men, and ALM = (0.6144 × (Ht²/Z₅₀)) + (−36.61 × (Z₂₅₀/Z₅)) + (−9332 × (1/Z₅₀)) + 37.91 for women. Additionally, we conducted measurements in 1624 men and 1368 women aged 18 to 40 years to establish sarcopenia cutoff values in the Japanese population. The mean values minus 2 standard deviations of the skeletal muscle mass index (ALM/Ht²) in these participants were 6.8 and 5.7 kg/m² in men and women, respectively. Conclusion: The current study established and validated a theoretical and age-independent equation using MF-BIA to estimate ALM and provided reasonable sarcopenia cutoff values.

As a chronic disease, osteoarthritis (OA) leads to degradation of both cartilage and subchondral bone, of which the development is related to proinflammatory cytokines like interleukin-1β. In the present study, the anti-inflammatory effect of Specnvezhenide in osteoarthritis and mechanism of it was studied in vitro and in vivo. The results showed that Specnvezhenide decreases interleukin-1β-induced expression of matix-degrading enzymes and reduces the activation of NF-κB and wnt/β-catenin pathways in vitro. Furthermore, Specnvezhenide treatment prevents the degeneration of both cartilage and subchondral bone in rats OA model. As conclusion, to the best of our knowledge, we report firstly that Specnvezhenide decreases interleukin-1β-induced inflammation on rat chondrocytes by inhibiting activation of NF-κB and wnt/β-catenin pathways, and has therapeutic potential in OA treatment.

There is evidence that optimal nutrition is fundamental to human health and in the prevention of non-communicable diseases (NCDs) later in adult life. The identification, production and consumption of functional foods worldwide can increase health benefits for all who can access and afford such foods subject to advice from nutritionists. Recent meetings organized by the health agencies, give a crucial opportunity to make nutrition, a central part of the post-2015 sustainable human and agricultural development agenda. The aim of discussions in these meetings was to provide functional crops and foods to achieve optimal health by prevention of NCDs. It is possible that these efforts might ensure that the goals and targets set in the agenda are adequate to address the many challenges of global undernutrition as well as obesity which are major risk factors of NCDs. In many developing and middle income countries, food security provided by the governments, in one sense understandably, gave least consideration to functional foods supply and the prevention of obesity and metabolic syndrome, resulting in to emergence of NCDs. The Thailand Declaration reiterates that commitments to eradicate hunger and undernutrition as well as over-nutrition, and to increase investments in effective interventions; designers foods and designers crops. However, in planning coherent policies, our past experience on rapidly absorbed, energy-rich processed foods should be taken in to account while developing sustainable food systems. The food industry should be educated to exploit the expertise of food scientists and health professionals in designing functional foods taking cognizance of manufacturing and processing. Similarly, agriculture scientists may be actively involved in educating farmers so as to grow cash crops providing functional foods. The aim should be to achieve an increase in the availability of functional foods to an extent, or by a policy, by which such foods are available to poors, at affordable cost to prevent hunger and undernutrition and related diseases as well as NCDs. In addition our efforts might help in developing an international consensus on how to approach the development of new designer foods by farmers and food industry to produce low glycemic index foods. Such efforts may establish an international framework for the prevention of NCDs, so that human susceptibility to these diseases is substantially diminished.

Suicidal behaviour remains difficult to predict and prevent, even for experienced mental health care professionals. The known distal risk factors for suicidal behaviour are not sufficiently specific to fully understand the complex dynamic processes that precede a suicide attempt. Real-time mobile monitoring data can be used to analyse proximal risk mechanisms within the suicidal process. At the same time smartphone-based safety planning and self-monitoring may enhance a patient’s self-management skills thereby increasing their capacity to respond to a suicidal crisis and to become more aware of crisis symptoms. The current paper describes the theoretical and conceptual rationale for the CASPAR study which applies an innovative approach to the study of suicidal processes. It uses basic science approaches to inform the implementation of an innovative suicide prevention intervention. We aim to develop and implement mobile safety plan in conjunction with real-time monitoring in order to both directly implement suicide prevention interventions and to study the ongoing dynamics of individual suicidal behaviour by applying network analysis.

The present paper offers a reading of three selected novels by two Anglophone Arab writers Diana Abujaber and Fadia Faqir. Our reading is fundamentally based on a philosophical post-humanist perception of other ethnic minorities as being inferior and un-human. In interpreting the three novels, Arabian Jazz (2003), My Name is Salma (2007) and Willow Trees Don’t Weep (2014), a main concern is to bring to light how Arabs –and Muslims –have been zombified and de-humanized in Western mainstream media and culture based on a biased stigmatization and stereotyping of a large heterogeneous ethnic group wherein religions, traditions, languages and cultures are diverse. Also, a pivotal preoccupation is going to be the exiling journey of the protagonists from their homelands to Western countries, and how these journeys contribute to the post-humanization of the self, the identity and the culture of Arab displaced immigrants.

Introduction Pedestrian road injuries are a significant public health issue in Georgia, Syria, and Tajikistan. This study investigates the trends in mortality, Years of Life Lost (YLLs), and incidence rates of pedestrian road injuries from 1990 to 2021, with a focus on sex-specific differences, using age-standardized data from the Global Burden of Disease (GBD) database. Methods The data for this analysis were obtained from the GBD database, emphasizing age-standardized rates of mortality, YLLs, and incidence of pedestrian-related road injuries in Georgia, Syria, and Tajikistan. The population was divided into male and female cohorts for comparison. Statistical methods included descriptive statistics, independent samples t-tests, and effect size calculations to evaluate the differences between sexes. Temporal trends were analyzed to observe changes over the study period. Results Mortality The analysis revealed that males had a significantly higher mean mortality rate (7.18, SD = 2.94) compared to females (2.26, SD = 0.78). The independent samples t-test confirmed a significant difference (t(62) = 9.141, p < 0.001). The effect sizes were substantial, with Cohen's d at 2.285, Hedges' g at 2.257, and Glass's Δ at 6.281. Over time, the mortality rates exhibited peaks in the early 1990s and mid-2000s, with a general decline afterward. Males consistently showed higher mortality rates than females throughout the period. YLLs (Years of Life Lost) For YLLs, males had a significantly higher mean rate (332.59, SD = 132.31) compared to females (103.35, SD = 32.57), with the t-test indicating a significant difference (t(62) = 9.515, p < 0.001). Effect sizes supported the significance of this difference, with Cohen's d at 2.379, Hedges' g at 2.350, and Glass's Δ at 7.308. The YLL rates showed notable peaks in the early 1990s and mid-2000s, followed by a decline, with males maintaining higher rates than females. Incidence Regarding incidence, males had a higher mean rate (235.90, SD = 36.09) compared to females (89.53, SD = 15.29). The t-test results (t(62) = 21.125, p < 0.001) and effect sizes (Cohen's d = 5.281, Hedges' g = 5.217, and Glass's Δ = 9.574) confirmed a significant difference between the sexes. Incidence rates demonstrated a significant decline from 1990 to 2000, followed by fluctuations, with males consistently experiencing higher rates than females. Conclusion This study underscores significant sex differences in mortality, YLLs, and incidence rates due to pedestrian road injuries in Georgia from 1990 to 2021, with males consistently showing higher rates. These findings emphasize the need for targeted interventions to address the specific vulnerabilities of male pedestrians in Georgia. The data and analysis were facilitated through collaboration with the Global Burden of Disease Study, whose contributions were invaluable.

This conceptual, interdisciplinary paper will start by introducing the commencement of a new era in which human society faces continuously accelerating technological revolutions, named for short ‘Padkos’. In this context, a conceptual model of sustainable development with a focus on knowledge sharing and management will be proposed. The construct of knowledge management will be unpacked into a three-layer model with a focus on the knowledge-human and data-machine spheres. Then, each sphere will be discussed with concentrating on the learning and decision- making processes, the digital supporting systems and the human actors’ aspects. Moreover, the recombination of new knowledge development and contemporary knowledge management into one amalgamated construct will be proposed. The holistic conceptual model of knowledge sharing for sustainable development is comprised by time, cybersecurity and two alternative humanistic paradigms (Homo Technologicus and Homo Sustainabiliticus). Two additional particular models are discussed in depth. First, a recently proposed model of quantum organizational decision-making is elaborated. Next, a boundary management and learning process is particularized. The paper ends with several implications for the future based on the deliberations in the paper and the models discussed.

The successful 2020 launch and 2021 landing of the National Aeronautics and Space Administration’s (NASA) Perseverance Mars rover initiated the first phase of the NASA and European Space Agency (ESA) Mars Sample Return (MSR) campaign. The goal of the MSR campaign is to collect scientifically interesting samples from the Martian surface and return them to Earth for further study in terrestrial laboratories. The MSR campaign consists of three major spacecraft components to accomplish this objective: the Perseverance Mars rover, the Sample Retrieval Lander (SRL) and the Earth Return Orbiter (ERO). Onboard the ERO spacecraft is the Capture, Containment and Return System (CCRS). CCRS will capture, process and return to Earth the samples that have been collected after they are launched into Mars orbit by the Mars Ascent Vehicle (MAV), which is delivered to Mars onboard the SRL. To facilitate the processing of the orbiting sample (OS) by CCRS we have designed and developed a vision system to determine the OS capture orientation. The vision system is comprised of two cameras sensitive to the visible portion of the electromagnetic spectrum and two illumination modules constructed from broadband light emitting diodes (LED). Vision system laboratory tests and physics-based optical simulations predict CCRS ground processing will be able to correctly identify the OS post-capture orientation using only a single vision system image that is transmitted to Earth from Mars orbit.

Two types of heterometallic (Fe(III),Na) silsesquioxanes [Ph₅Si₅O₁₀]₂[Ph₁₀Si₁₀O₂₁]Fe₆(O^2‒)₂Na₇(H₃O⁺)(MeOH)₂(MeCN)_4.5.1.25(MeCN), I, and [Ph₅Si₅O₁₀]₂[Ph₄Si₄O₈]₂Fe₆Na₆(O^2‒)₃(MeCN)_8.5(H₂O)_8.44, II, were obtained and characterized. X-Ray studies established distinctive structures of both products, with pair of Fe(III)-O-based triangles surrounded by siloxanolate ligands, giving fascinating cage architectures. Complex II proved to be catalytically active in the formation of amides from alcohols and amines, thus becoming a rare example of metallasilsesquioxanes performing homogeneous catalysis. Benzene, cyclohexane and other alkanes, as well as alcohols, can be oxidized in acetonitrile solution to phenol, the corresponding alkyl hydroperoxides and ketones, respectively, by hydrogen peroxide in air in the presence of catalytic amounts of complex II and trifluoroacetic acid. Thus, the cyclohexane oxidation at 20 °C gave oxygenates in very high for alkanes yield (48% based on alkane). The kinetic behaviour of the system indicates that the mechanism includes the formation of hydroxyl radicals generated from hydrogen peroxide in its interaction with diiron species. The latter are formed via monomerization of starting hexairon complex with further dimerization of the monomers.

This paper proposes an omnidirectional conveyor as a novel alternative to existing omnidirectional conveyors. With symmetric and compact layout, this new structure ensures consistent kinematics and enhanced flexibility in trajectory planning. The kinematic model of the proposed omnidirectional conveyor is developed and verified through simulation in CoppeliaSim. Four typical classes of trajectories are generated and verified in the simulation environment. Using PID control, the actual trajectories of a package on the conveyor closely match the desired trajectories. In addition, this paper outlines the workspace and corresponding wheel patterns for the conveyor, demonstrating how different supported wheel patterns emerge when packages move across various areas of the conveyor. The discussion extends to fault tolerance and obstacle avoidance, examining the workspace and wheel patterns with one or two omni wheels failed. Furthermore, this paper provides a comprehensive analysis on the feasible desired movements for the packages on the conveyor under the constrained wheel speed. This provides insights and guidance on trajectory planning and design of the conveyor.

Generic text embeddings have demonstrated considerable success across a multitude of applications. However, these embeddings are typically derived by modeling the co-occurrence patterns within text-only corpora, which can limit their ability to generalize effectively across diverse contexts. In this study, we investigate methodologies that incorporate visual information into textual representations to overcome these limitations. Through extensive ablation studies, we introduce a novel and straightforward architecture named VisualText Fusion Network (VTFN). This architecture not only surpasses existing multimodal approaches on a range of well-established benchmark datasets but also achieves state-of-the-art performance on image-related textual datasets while utilizing significantly less training data. Our findings underscore the potential of integrating visual modalities to substantially enhance the robustness and applicability of text embeddings, paving the way for more nuanced and contextually rich semantic representations.

You Only Look One (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. However, because of the diverse characteristics of YOLO models, choosing selecting the optimal model according to various applications and environments in smart transportation is critical. In this article, we conduct an empirical evaluation and analysis study for most YOLO versions to assess their performance in smart transportation. To achieve this, we first measure the average precision of YOLO models across multiple datasets (e.g., COCO, PASCAL VOC). Second, we analyze the performance of YOLO models on multiple object categories within each dataset, focusing on classes relevant to road transportation such as those commonly used in smart transportation applications. Third, multiple intersection-over-union (IoU) thresholds are considered in our performance measurement and analysis. By examining the performance of various YOLO models across datasets, IoU thresholds, and object classes, we make six observations on these three aspects while aiming to identify optimal models for road transportation scenarios. Thus, YOLOv5 and YOLOv8 outperform other models in all three aspects due to their novel performance features. For instance, YOLOv5 achieves stable performance thanks to its cross-stage partial darknet-53 (CSPDarknet53) backbone, auto-anchor mechanism, and efficient loss functions including IoU loss, complete IoU loss, focal loss, gradient harmonizing mechanism loss. Similarly, YOLOv8 outperforms others with its upgraded CSPDarknet53 backbone, anchor-free mechanism, and efficient loss functions like complete IoU loss and distribution focal loss.

This study examines the transformative potential of Artificial Intelligence (AI) in international trade, highlighting its significant roles in optimizing trade operations, enhancing trade finance, and improving market access. In trade optimization, through advanced machine learning and predictive analytics, AI helps in demand forecasting, route optimization, and customs processes, ensuring efficient logistics and inventory management. In trade finance, AI automates document processing and risk assessment, democratizing access to finance and enhancing transactional transparency through integration with blockchain technology. In improving market access, AI-driven analytics identify consumer trends and competitive dynamics, enabling personalized marketing and overcoming linguistic and cultural barriers. The study includes case studies of leading companies such as Alibaba, DHL, and Maersk, showcasing how they leverage AI to enhance their trade operations, improve customer service, and achieve greater efficiency. These real-world examples demonstrate AI's practical applications and significant benefits in the global trade landscape. However, the adoption of AI in international trade is not without challenges. These include data quality, ethical considerations, technological complexity, and public perception. Ensuring high-quality, accessible data, fostering ethical AI usage, and overcoming technological and regulatory barriers are crucial for successful AI integration. Policy recommendations emphasize the need for robust data infrastructure, ethical AI guidelines, and international cooperation to harmonize data protection regulations. These measures aim to create an environment conducive to AI-driven sustainable economic growth and innovation in global trade.

The dynamics of society is enabled, in large part, through an efficient matching between people who have money to lend and people who have a need to borrow. Fair loans serve both the lender and the borrower. This task is handled today mostly via traditional banks. They offer various plans to depositors from whence they serve borrowers. Proposing to replace such rigidity with cyberspace-rooted dynamic ad-hoc global matching of lenders and borrowers. Uniquely here we build a chain of lenders to support a single borrower. Lenders will post a proposition to lend a given amount of money for a stated duration for a set interest rate. Borrowers will post a request to borrow a desired amount of money, for a specified duration, and for which they are ready to pay a stated interest. A virtual digital bank (VDB) will match all the posts, negotiate terms as necessary, and move the money -- everyone benefits. Distributed Digital Lending, DDL, applies to macro, long terms loans, as well as to micro. very short terms loans. DDL efficiency will ensure that all money at rest will be money in growth, and the full global lending capacity will be put to good service through the exact loans borrowers want. DDL is hinged in digital transactions which are immediate, irrevocable, and private, per regulatory allowance. The matching is optimized with AI tools. BitMint*LeVeL is the design standard coin for DDL, but other digital money options will do too.

The advent of the digital age has introduced unprecedented opportunities for communication and connectivity, but it has also given rise to new forms of harassment, collectively termed cyber harassment. This research article provides an in-depth exploration of cyber harassment, examining its prevalence, the profound impact it has on victims, and potential solutions to mitigate its effects.The study is structured around three primary research objectives. Firstly, it investigates the psychological impact of cyber harassment on victims, highlighting the severe emotional and mental health consequences that can arise from such abuse. Secondly, the article scrutinizes the role of social media platforms in both facilitating and combating cyber harassment, analyzing how these platforms can act as both enablers of harassment and as venues for intervention. Thirdly, the research evaluates the current legal frameworks and responses to cyber harassment, considering their effectiveness and suggesting possible improvements. Recent research findings and diverse methodologies are integrated to provide a comprehensive understanding of the multi-faceted nature of cyber harassment. By addressing these key areas, the article aims to contribute to the development of more effective strategies to prevent and respond to cyber harassment, ultimately fostering a safer online environment.

Objective: This study aimed to analyze the general characteristics, job stress, burnout, and turnover intentions of Clinical Research Associates (CRAs). Our objective was to provide a reference point for devising strategies to reduce CRA turnover and burnout rates. Methods: A descriptive, quantitative, and correlative research design was used. A total of 126 CRAs completed a questionnaire that consisted of 115 items, with 21 items on general characteristics, 60 items on occupation-al role, and 10 items on personal strain in job stress. The Burnout Inventory scale was used to investigate 22 items of burnout, and turnover intentions was measured using a 5-item scale. Results: Of the 126 participants, 63 (50%) answered that they intended to leave their job within 1 year & the most of participants were nurse (n = 56, 44.4%). Job stress related to the occupational role of CRA’s vocational stress (r = 0.518), burnout (r = 0.406), and turnover intention (r = 0.181) of personal strain were correlated with each other. Job stress due to personal strain had an explanatory power of 18.7% as a factor influencing turnover intention. Conclusions: To reduce the turnover intention of CRAs, who play an important role in clinical research, it is necessary to find ways to re-duce job stress and burnout.

Geothermal energy generation faces challenges in efficiency, partly due to restrictions on reinjection temperatures caused by scaling issues. Therefore, developing strategies to prevent scaling is critical. This study aims to simulate the scaling tendencies and corrosion effects of geothermal fluids on various construction materials used in scaling reactor/retention tank systems. A range of materials, including carbon steel, austenitic stainless steel, duplex stainless steel, two proprietary two-part epoxy coatings, and thermally sprayed aluminium (TSA), were tested in a simulated geothermal brine. Experiments were conducted in a laboratory vessel designed to replicate the wall shear stress conditions expected in a scaling reactor. The tests revealed varying scaling tendencies among the materials, with minimal corrosion observed. The dominant scale formed was calcium carbonate, consistent with geochemical modelling. The findings suggest that despite the high operating temperatures, the risk of corrosion remains low due to the brine's low chloride content, while the wettability of materials after immersion may serve as a useful indicator for selecting those that promote scaling.

This paper introduces the novel concept of Time-Traveling Turing Machines (TTTMs) — Turing Machines with the ability to read symbols that have been explicitly sent from their future computational state. We delve into their properties and behavior, particularly emphasizing the importance of maintaining a self-consistent computational timeline. We present theorems demonstrating the universality of these machines and the challenges in achieving faster computations than traditional Turing Machines.

This study presents the development and implementation of a remote monitoring system for a dual-axis solar tracker, integrating Industry 4.0 technologies such as IoT, SCADA, and MQTT. The system, which combines a Siemens S7-1200 PLC, an IoT gateway, and a SCADA platform based on Ignition, demonstrated significant increases in solar capture efficiency, with production gains of 25-30% compared to fixed systems, reaching up to 67.65% under ideal conditions. In addition to improving operational management through predictive monitoring and early fault detection, the study identified areas for improvement, such as the need for real-world testing and the integration of weather predictions. In conclusion, the research validates the feasibility and effectiveness of automated IoT and SCADA-based systems to optimize solar trackers, significantly contributing to improved energy efficiency in photovoltaic installations.

Peptidergic GPCR systems are broadly distributed in the human body and regulate numerous physiological processes by activating complex networks of intracellular biochemical events responsible for cell regulation and survival. Their failure due to overaction, ill-function, or blockade gives rise to cell disturbances, eventually causing disease if compensatory mechanisms do not suffice. Revision of updated experimental research provided an evident relationship associating peptidergic GPCR malfunction with tumor formation and maintenance resulting from uncontrolled cell proliferation and migration, colonization, inhibition of apoptosis or altered metabolism, and increased angiogenesis in tumoral tissues. Determination of the implication of GPCR peptide signaling in specific neoplasia is crucial to designing tailored pharmacological treatments to counteract or dismantle the origin of the signaling circuitry causing cellular disruption. In some cases, particular ligands for these receptors may serve as concomitant treatments to aid other pharmacological or physical approaches to eradicate neoplasias.

Optical Coherence Tomography (OCT) is a non-invasive diagnostic technique that renders an in vivo cross-sectional view of the retina. OCT utilizes a concept known as interferometry to create a cross-sectional map of the retina that is accurate to within at least 10-15 microns. Due to the transparency of the eye, OCT has gained wide popularity as an ophthalmic diagnostic tool. The OCT pictures of the retina are classified into “AMD, CNV, DRUSEN, DMR, DR, MH, CSR, and Normal Eye” using a lightweight deep neural network. There are two types of FD-OCT – swept-source OCT (SS-OCT) and spectral-domain OCT (SD-OCT) – both of which acquire spectral interferograms which are then Fourier transformed to obtain an axial scan of reflectance amplitude versus depth. Normal OCT features show a clear and defined retinal structure. The random forest algorithm is a robust ML algorithm that can be used to classify OCT images into four classes: choroidal neovascularization (CNV), deep margin elevation (DME), drusen, and normal. OCT (Optical coherent tomography) is an imaging method used to generate a picture of the back of the eyes and retinas. By using an interferometer, part of the light is directed to the sample and another portion is sent to a reference arm with a well-known length. Interferometers merge two or more sources of light to create interference patterns. We split the light into two beams that travel different optical paths and are combined to produce interference. Optical coherent tomography (OCT) generates sub-surface images of translucent or opaque materials at a resolution equivalent to a low power microscope. OCT build up clear 3D images of thick samples by rejecting background signals whilst collecting light directly reflected from a surface of interest. OCT systems use broadband sources and split light in a fiber coupler, first on a direct reference mirror, and as the sample is being measured. Balanced OCT systems can include additional attenuators at the detector arm to improve the detection efficiency.

Harvesting is the collection of mature crops from the field. A harvesting procedure involves cutting, installation, collecting, transferring, and then stacking the cut produce. Mechanization of harvesting operations is critical to lowering harvesting costs, crop production costs, crop loss, turnaround time, weather risk, and increasing benefit through proper technology. To achieve the desired purpose, a manually operated reaper machine is created and developed to assist farmers by lowering the cost of crop cutting and collection in the field while achieving the best efficiency possible within the limits. Research technique is a set of acts or procedures that must be completed in order to do research properly, as well as the intended sequence of these steps. Identify the problem statement. Studying the current design of the reaper machine Review the literature. Product development general design process steps for reaper harvester’s machine include planning, concept development, system-level design, detail design, testing and refining, and product ramp-up. In this step, the material properties are defined based on design. To simulate the reaper machine using Catia software, Prototyping, testing for validation, Interpret and report. Material is chosen based on the strength requirements of the different parts of the Reaper machine. The machine is built with locally accessible materials. This self-propelled reaper moves at a forward speed of 2.54 m/s. The cutting bar measures 120 cm in length and the bundling mechanism is dropped. The field capacity is 0.306 ha/hour, respectively. The needed manpower for harvesting one hectare of wheat and rice reaper harvesting field operation is two man-hours per ha. The amount of fuel required to completely fill the tank after harvesting the plot was measured to determine the amount of fuel consumed for reaping the test plot, which was 1.17 l/h.

Flavonoids are secondary plant metabolites involved in biological activity that are present in plentiful proportions in many plant origin foods and beverages. Owing to their chemical difference and qualities that make them beneficial for human health, they have received a lot of focus in research. This review therefore presents an account on the chemical structure of flavonoids, food sources and their metabolism with emphasis on bioavailability. And they also examine their antioxidant, anti-inflammatory, anticancer, cardiovascular protective, neuroprotective, and antimicrobial properties and reveal related molecular processes. In addition, it overviews the clinical data concerning their possible use in the prevention and treatment of chronic diseases. Some of the problems that attend current flavonoid research are also dealt with; such issues as variation in the bioactivity of flavonoids and scarcity of clinical studies. This review is designed to present current state of knowledge and to provoke further research concerning the further potential of flavonoids in enhancing human health.

This research explores how regional socioeconomic variables affect the perception of social trust and support networks (PYCC) in Italian regions, and examines the implications for public policy designed to strengthen social cohesion. This study examines the variable "People You Can Count On" (PYCC) from the ISTAT-BES dataset, focusing on its distribution across Italian regions between 2013 and 2022. Using clustering through a k-Means algorithm optimized with the Silhouette coefficient and the Elbow method, three distinct clusters of regions emerged, highlighting significant differences in social support networks. An econometric model was employed to estimate the PYCC variable, factoring in socioeconomic indicators such as employment rates, income inequality, and social participation. The results indicate a complex interplay between socioeconomic conditions and social trust, with regions in the South and Islands showing increased community support, while many Northern regions experienced declines. The study suggests that areas with lower economic conditions often foster stronger social networks, driven by necessity. These findings underline the importance of targeted public policies aimed at fostering social cohesion, particularly in regions facing economic challenges. Policy implications include enhancing education, supporting small enterprises, and promoting social housing and welfare initiatives. Strengthening community participation and volunteering are also highlighted as critical strategies to build resilient support networks. Overall, the research provides valuable insights into the regional disparities of social trust and the role of socioeconomic factors in shaping community support across Italy.

The chronic high fat dysbiosis diet (HFD) instigates cardiac remodeling, dysfunction and chronic heart failure (CHF). The therapeutic approaches focusing oxidative stress, inflammation and hyperlipidemia have not yielded significant positive clinical outcomes. Recent studies report that although mitochondrial ATP citrate lyase (ACLY) supports cardiac function, however, decreases more in human HFpEF than HFrEF. Interestingly, the ACLY synthesizes lipids and creates hyperlipidemia. Epigenetically, ACLY acetylates histone. The mechanism(s) are unknown. One hypothesis is that the HFD induces epigenetic folate 1-carbon metabolism (FOCM), heperhomocysteinemia (HHcy, a cause of abrogation of sleep-time dipping in blood pressure and hypertension) and heart failure. Interestingly, the probiotics utilizes the fat/lipids post-biotically, and increases the mitochondrial bioenergetics and attenuates the HFD induced heart failure. We suggest a novel and paradigm-shift epigenetic mitochondrial sulfur transsulfuration pathways that selectively target HFD-induced CHF. The HFD via transport and metabolomic pathways instigates cardiac remodeling and dyfunction. Previous studies from our laboratory, using a single cell analysis, revealed increase in transporter (SLC25A) of s-adenosine-methionine (SAM) during elevated levels of homocysteine (Hcy, i.e., hyperhomocysteinemia, HHcy), a consequence of impaired epigenetic recycling of Hcy back to methionine by increase in FOCM methylation of H3K4, K9, H4K20 and gene writer (DNMT) and decrease in eraser (TET/FTO). The Hcy transported to mitochondria by SLC7A for clearance via sulfur metabolomic transsulfuration by 3-mercaptopyruvate sulfur transferase (3MST). Interestingly, the HHcy decreases ATP, OCR, H₂S, PGC1α, TFAM, and increase in fission/fusion ratio, causing mitochondria dysfunction. We suggest that gut dysbiosis by HFD disrupts rhythmic epigenetic memory via FOCM and increase in DNMT1 and creates HHcy, leading to decrease mitochondrial transsulfuration and bioenergetics. The treatment with a probiotic, lactobacillus will eat the fat/lipids post-biotically and bi-directionally will produce folic acid and lactone-ketone body that will mitigate the HFD-induced mitochondrial remodeling and heart failure.

Atherosclerosis is a leading cause of cardiovascular disease, characterized by lipid accumulation and chronic inflammation within arterial walls. Early detection in young adults is crucial for preventing adverse cardiovascular events. This study investigates the associations between inflammatory indices, lipid biomarkers, and the presence of atherosclerosis in patients aged 18 to 55 years. Methods: A cross-sectional study was conducted involving 89 participants divided into two groups: 62 patients with documented atherosclerosis (main group) and 27 healthy controls without significant atherosclerosis. Comprehensive data—including demographic information, medication use, imaging results, laboratory parameters, and calculated inflammatory indices (SIRI, SII, AISI, NLR, PLR, MLR)—were collected. Statistical analyses included correlation assessments, group comparisons using the Mann-Whitney U test, logistic regression modeling, feature importance analysis with Random Forest and Gradient Boosting classifiers, receiver operating characteristic (ROC) curves, and K-means clustering. Results: Significant differences were observed between the main and control groups. Patients with atherosclerosis exhibited elevated inflammatory indices (SIRI, NLR, MLR, SII) and lipid profile abnormalities (higher TC and LDL-C, lower HDL-C). Lp(a) and ANGPTL3 levels were significantly higher in the main group (p < 0.001 and p < 0.01, respectively). Logistic regression identified SIRI and ANGPTL3 as significant predictors of atherosclerosis, with the model demonstrating high accuracy (77%) and sensitivity (93%). Feature importance analysis confirmed the significance of SIRI and ANGPTL3, alongside traditional lipid biomarkers, in predicting disease presence. ROC analysis showed excellent model performance (AUC > 0.80). Clustering analysis revealed two distinct patient subgroups characterized by predominant inflammatory profiles or lipid metabolism disturbances. Conclusions: Systemic inflammation and lipid abnormalities play significant roles in early atherosclerosis among young adults. Elevated SIRI and ANGPTL3 levels are potent predictors of disease presence. The integration of inflammatory indices and lipid biomarkers into predictive models enhances risk stratification and supports personalized medicine approaches. Further research with larger cohorts is warranted to validate these findings and inform targeted prevention and intervention strategies.

The availability of petroleum asphalt, derived from non-renewable sources, is steadily declining alongside diminishing petroleum reserves. To reduce reliance on petroleum, alternative renewable natural sources are being explored as both modifiers and replacements for petroleum asphalt, particularly in asphalt binders. This study explores the chemical, rheological, and mechanical properties of Gopal, a bio-asphalt derived from Gondorukem (gum rosin) and crude palm oil (CPO). Two Gopal variants, Gopal-GEM130 and Gopal-GEG90, were analyzed using FTIR and EDX methods, with Pen 60 petroleum asphalt as a control. The results reveal that Gopal-GEG90 and Gopal-GEM130 exhibit 86% chemical similarity to Pen 60 asphalt. Gopal-GEM130 is less toxic and less alkaline compared to Pen 60, while Gopal-GEG90 is less toxic but more alkaline. Both variants fall under the same classification as Pen 60 in terms of rheological properties, with Gopal-GEG90 demonstrating slightly better stripping resistance but lower aging resistance. Gopal-GEM130 showed better stripping resistance and rutting performance, though with lower fatigue resistance and faster aging compared to Pen 60 asphalt. Both bio-asphalt variants align with performance grade PG64S, signifying their potential as alternatives to conventional petroleum asphalt.

Serious crime modelling typically needs to be undertaken securely behind a firewall where police knowledge and capabilities can remain undisclosed. Data informing an ongoing incident is often sparse, with a large proportion of relevant data only coming to light after the incident culminates or after police intervene - by which point it is too late to make use of the data to aid real-time decision making for the incident in question. Much of the data that is available to police to support real-time decision making is highly confidential so cannot be shared with academics, and is therefore missing to them. In this paper, we describe the development of a formal protocol where a graphical model is used as a framework for securely translating a model designed by an academic team to a model for use by a police team. We then show, for the first time, how libraries of these models can be built and used for real-time decision support to circumvent the challenges of data missingness and tardiness seen in such a secure environment. The parallel development described by this protocol ensures that any sensitive information collected by police, and missing to academics, remains secured behind a firewall. The protocol nevertheless guides police so that they are able to combine the typically incomplete data streams that are open source with their more sensitive information in a formal and justifiable way. We illustrate the application of this protocol by describing how a new entry - a suspected vehicle attack - can be embedded into such a police library of criminal plots.

Gut dysbiosis and an inflamed bowel are growing concerns in mammals, including dogs. Probiotic supplements have been used to restore the natural microbial community and improve gastrointestinal health. Biofilm formation, antimicrobial activities, and immunological responses of probiotics are crucial to improving gut health. Thus, we tested a commercial probiotic blend (LabMAX-3), a canine kibble additive comprising Lactobacillus acidophilus, Lacticasibacillus casei, and Enterococcus faecium for their ability to inactivate common enteric pathogens; their ability to form biofilms, epithelial cell adhesion and anti-inflammatory response on Madin-Darby Canine Kidney (MDCK) cell line. Probiotic LabMAX-3 blend, or individual isolates, showed a strong inhibitory effect against Salmonella enterica, Listeria monocytogenes, enterotoxigenic Escherichia coli, and Campylobacter jejuni. LabMAX-3 formed biofilms comparable to Staphylococcus aureus. LabMAX-3 adhesion to the MDCK cell line (with or without lipopolysaccharide, LPS) pretreatment showed comparable adhesion and biofilm formation (p < 0.05) to L. casei ATCC 334 used as a control. LabMAX-3 had no cytotoxic effects on the MDCK cell line during 1 h exposure. The IL-10 and TNFα ratio of LabMAX-3, compared to the L. casei control, showed a significant increase (p < 0.05), indicating a more pronounced anti-inflammatory response. The data show that LabMAX-3, a canine kibble supplement, can improve gastrointestinal health.

Lignin is nature's second most abundant vascular plant biopolymer, playing significant roles in mechanical support, water transport, and stress responses. This study identified 90 lignin biosynthesis genes in the rice based on phylogeny and motif constitution, and they belong to PAL, C4H, 4CL, HCT, C3H, CCoAOMT, CCR, F5H, COMT, and CAD families. Duplication events contributed largely to the expansion of these gene families, such as PAL, CCoAOMT, CCR, and CAD families mainly attributed to tandem and segmental duplication, respectively. Microarray data of 33 tissue samples covering the entire life cycle of rice suggested, fairly high PAL, HCT, C3H, CCoAOMT, CCR, COMT, and CAD gene expression, and rather variable C4H, 4CL, and F5H expression. Some members of lignin-related genes (OsCCRL11, OsHCT1/2/5, OsCCoAOMT1/3/5, OsCOMT, OsC3H, OsCAD2, and OsPAL1/6) were expressed in all tissues examined. The expression patterns of lignin-related genes can be divided into two major groups with eight subgroups, each showing a distinct co-expression in tissues representing typically primary and secondary cell wall constitutions. Some lignin-related genes were strongly co-expressed in tissues typical of secondary cell walls. The combined HPLC analysis showed increased lignin monomers (H, G, and S) in five genotypes from young to old growth stages. Based on 90 genes' microarray data, 27 genes were selected for qRT-PCR gene expression analysis. Four genes (OsPAL9, OsCAD8C, OsCCR8, and OsCOMTL4) were significantly negatively correlated with lignin monomers. Furthermore, eleven genes were co-expressed in certain genotypes during secondary growth stages. Among them, six genes (OsC3H, OsCAD2, OsCCR2, OsCOMT, OsPAL2, and OsPAL8) were overlapped with microarray gene expressions, highlighting their importance in lignin biosynthesis.

The spread of false information can significantly harm public opinion, underscoring the importance of accurately identifying untrustworthy news. This paper presents an innovative machine learning (ML) tool, TMining, designed to evaluate news credibility and facilitate various text-mining tasks. By examining a range of ML methodologies alongside preprocessing techniques, we aim to boost the system's effectiveness. Our research meticulously assesses different datasets, highlights the impact of applying stemming techniques, and employs Local Interpretable Model-Agnostic Explanations (LIMEs) to shed light on the rationale behind model predictions. The outcomes reveal a notable enhancement in both the precision and clarity of the news verification process. The ultimate version of the model has been made available as an Application Program Interface (API), and its source code has been shared openly, encouraging further exploration and collaboration within the scientific community. This initiative advances our ability to discern manipulative context from fictitious content and promotes transparency and understanding in the domain of ML applications.

Late-stage epithelial ovarian cancer (EOC) involves widespread dissemination of malignant disease throughout the peritoneal cavity, often accompanied by ascites. EOC metastasis relies on the formation of multicellular aggregates, called spheroids. Given that Liver Kinase B1 (LKB1) is required for EOC spheroid viability and LKB1 loss in EOC cells decreases tumor burden in mice, we investigated whether the LKB1 complex controls invasive properties of human EOC spheroids. LKB1 signalling was antagonized through CRISPR/Cas9 genetic knockout of LKB1 and/or RNAi-dependent targeting of STE20-related kinase adaptor protein (STRAD; an LKB1 activator). EOC spheroids expressing nuclear GFP (green) or mKate2 (red) constructs were embedded in Matrigel for real-time live-cell invasion monitoring. Migration and invasion were also assessed in spheroid culture using Transwell chambers, spheroid reattachment, and mesothelial clearance assays. The loss of LKB1 and STRAD signalling decreased cell invasion through Matrigel and Transwell membranes, as well as mesothelial cell clearance. In the absence of LKB1, zymographic assays identified a loss of matrix metalloproteinase (MMP) activity, whereas spheroid reattachment assays found that coating plates with fibronectin restored the invasive potential. A three-dimensional EOC organoid model demonstrated that organoid area was greatly reduced by LKB1 loss. Overall, our data indicated that LKB1 and STRAD facilitated EOC metastasis by promoting MMP activity and fibronectin expression. Given that LKB1 and STRAD are crucial for EOC metastasis, targeting LKB1 and/or STRAD could disrupt the dissemination of EOC, making inhibitors of the LKB1 pathway an alternative therapeutic strategy for EOC patients.

The last wave of Artificial Intelligence is dedicating particular emphasis to the line of explainability research. The potential of Explainable Artificial Intelligence (XAI) in producing trustworthy computer-aided-diagnosis systems and its usage for knowledge discovery are collecting interest in the Medical Imaging (MI) community to support the diagnostic process and the discovery of image biomarkers. Most of the existing XAI applications in MI were focused on interpreting the predictions returned by deep neural networks, typically including attribution techniques with saliency map approaches and other feature visualization methods. However, these are often criticized for providing incorrect and incomplete representations of the black-box models’ behaviour. This raises the attention in proposing models intentionally designed to be self-explanatory. In particular, part-prototype (PP) models are interpretable-by-design computer vision (CV) models that base their decision process in learning and identifying representative prototypical parts from the input images, and they are collecting increasing interest and results in MI applications. This narrative review provides a summary of existing PP networks, their application in MI analysis and current challenges.

This review explores the transformative role of artificial intelligence (AI) in the entire winemaking process, from viticulture to bottling, with a particular focus on enhancing food safety and traceability. It discusses AI’s applications in optimizing grape cultivation, fermentation, bottling, and quality control, while emphasizing its critical role in managing microbiological risks such as mycotoxins. The review aims to show how AI technologies not only refine operational efficiencies but also raise safety standards and ensure traceability from vineyard to consumer. Challenges in AI implementation and future directions for integrating more advanced AI solutions into the winemaking industry will also be discussed, providing a comprehensive overview of AI's potential to revolutionize traditional practices.

This study investigates the impact of Artificial Intelligence (AI) on traditional firms, specifically examining how scalable network properties and the integration of Environmental, Social, and Governance (ESG) considerations affect financial margins, sustainability, and bankability. The research addresses the core question of how AI investments can drive economic value by enhancing EBITDA and financial stability while aligning firms with sustainability goals. Using advanced network theory and multilayer models, the study reveals that AI-driven scalability significantly improves a firm's financial performance, making it more attractive to investors and financial institutions. Additionally, the integration of ESG factors further enhances operational efficiency, market valuation, and long-term financial stability. The study introduces an innovative "with-or-without" analysis to quantify the comparative benefits of AI and ESG integration, underscoring the role of these technologies in driving sustainable growth and addressing bankability concerns in traditional firms. This comprehensive approach offers new insights into the evolving dynamics of AI, ESG, and corporate finance.

Sleep disturbances and chronic pain are prevalent and interrelated conditions that significantly impact individuals' quality of life. Understanding the intricate dynamics between sleep and pain is crucial for developing effective treatments that enhance the well-being of affected individuals and reduce the economic burden of these debilitating conditions. This narrative review examines the complex relationship between sleep disturbances and chronic pain. We describe the prevalence and types of sleep disturbances and sleep disorders in chronic pain patients. Posteriorly we critically review the clinical and experimental evidence investigating the relationship between sleep disturbances and chronic pain aiming to clarify the impact of chronic pain on sleep and, conversely, the impact of sleep disturbances on pain perception. We conclude that a bidirectional relationship between chronic pain and sleep disturbances is almost a consensus in the literature, however, the strength of each direction of the association is less clear. As of now, the literature suggests that sleep impairment is a stronger predictor of pain than pain is a predictor of sleep impairment. Additionally, addressing sleep disturbances in chronic pain patients is crucial, as poor sleep has been linked to higher levels of disability, depression, and pain-related catastrophizing.

Recent epidemiologic studies have revealed an upward trend in young-onset colorectal cancer (YOCRC) overall, whereas specific data on young-onset colorectal neuroendocrine neoplasms (YONEN) remain limited. This study investigates demographic characteristics and survival trends in YONEN and compares these with those of young-onset colorectal adenocarcinoma (YOADC), the most common histologic subtype of YOCRC. A retrospective analysis was conducted from 2000 to 2019 using the Surveillance, Epidemiology, and End Results (SEER) database. Survival outcomes were assessed using univariate and multivariable Cox proportional models, with demographic differences evaluated via Wilcoxon Rank Sum and Chi-square tests. Out of 61,705 patients aged 20-49 with colorectal cancer, 8% had NEN, and 92% had adenocarcinoma. The YONEN cohort had a higher proportion of Black patients and a lower proportion of White patients than the YOADC cohort (21% vs. 13% and 44% vs. 57%, respectively). NEN was more commonly found in the rectum (79%), and adenocarcinoma was mostly colonic (57%) in origin. YONEN patients had better survival than YOADC patients. Multivariate analysis in YONEN patients revealed that Hispanic patients had better overall survival compared to White patients (HR 0.67, 95% CI 0.47-0.95, p=0.024). Racial disparities should be investigated further to aid in policymaking and targeted interventions.

Introduction: Patients with hematological malignancies undergo intensive treatment and prolonged hospitalization, thus having a variety of physical and psychosocial symptoms and worse quality of life (QOL). Aim: This study aimed to assess the QOL and investigate the symptoms of hospitalized hematological cancer patients. Methods: A cross-sectional study was conducted in the hematology clinics and day units of two general hospitals of Heraklion, Crete. Adult patients with hematological malignancy and an adequate understanding of the Greek language participated. A demographic questionnaire, the European Organization for Research and Treatment for Cancer quality assessment questionnaire (EORTC QLQ-C30), and the MD Anderson Symptom Inventory (MDASI) were used for data collection. The level of statistical significance was set at p &lt;0.05. Results: The sample consisted of 120 patients, 42.5% of whom were women, with a mean age of 65.6 years. The mean time from diagnosis was 33 months. The global health status of QoL had an average value of 47.1. The highest levels of QOL were found in the subscale of cognitive function (72.8) and the lowest in the role function (46.1). Among the of EORTC QLQ-C30 symptoms scale, the lowest score was found in nausea-vomiting (11.0) and the highest in fatigue (59.1). In the MDASI, in part I (core symptoms), higher levels, but also medium intensities were reported at fatigue (78.3%, mean 3.5), drowsiness (65.0, mean 3.3), and distress (65.8%, mean 2.8). In part II, enjoyment of life (85.8%, mean 5.1) had the highest and relation with other people (67.5%, mean 3.7) the lowest scores. The increase in the severity of the core symptoms (part I) was related to females (rho = 0.193, p &lt;0.05) and comorbidities (rho = 0.220, p &lt;0.05). It also related to a significant decrease in all functional domains and an increase in fatigue (rho = 0.571, p &lt;0.05) of the EORTC QLQ-C30 questionnaire. The increased global health status was related to males (rho = -0.185, p &lt;0.05) and physical functioning with younger age (rho = -0.331, p &lt;0.05), higher education (rho = 0.239, p &lt;0.05), fewer months from diagnosis (rho = -0.199, p &lt;0.05) and low comorbidity (rho = -0.209, p &lt;0.05). Finally, the increased global health status was significantly related to lower symptoms determined by the total average symptom score (-0.491, p &lt;0.05). Conclusions: The QoL of hematological cancer patients is significantly decreased during treatments due to a significant number of symptoms that must be taken into consideration for high-quality individualized care.

Minimizing optical losses in resonant cavities is crucial for improving photonic device performance. This study focuses on the development of a simulation tool to analyze scattering losses in Fabry-Pérot interferometers (FPI), offering precise modeling of waveguide dynamics and contributing to accurate loss predictions across various platforms. Optical cavities often suffer from scattering losses due to surface roughness and material defects. Our approach integrates theoretical models and simulations to quantify these losses, utilizing the FPI as a model system. We identified upper and lower reflectivity thresholds, beyond which accurate measurement of losses becomes unreliable. For reflectivity below a certain threshold, measurement errors arise, while excessively high reflectivity can reduce fringe visibility and introduce detector sensitivity issues. Simulations were used to validate the model's ability to predict reflectivity and attenuation in waveguides with varying loss levels. The software’s flexibility to adjust transmission parameters for different cavity configurations enhances its utility for a broad range of photonic systems. Our study offers a novel methodology for optical loss analysis, with practical applications in optimizing photonic devices. By providing a reliable tool for precise loss measurement, this work supports advancements in optical technologies, enabling the design of more efficient, high-performance devices across various applications.

This thesis presents a comprehensive review of cancer, with a particular focus on its physical and biochemical basis. Cancer, a leading cause of mortality worldwide, is characterized by the uncontrolled growth and spread of abnormal cells. Understanding the fundamental differences between cancerous and normal cells is essential for developing effective diagnostic tools and therapeutic strategies. The review begins by exploring the physical anomalies of cancer cells, including their irregular shape, size, and structural organization. These cells often exhibit altered cell membranes, disrupted cytoskeletal architecture, and irregularities in cell adhesion and communication, which contribute to their invasive and metastatic potential. The biochemical basis of cancer is examined in detail, with an emphasis on the dysregulation of key metabolic pathways. Cancer cells undergo profound metabolic reprogramming, often referred to as the Warburg effect, where they preferentially utilize glycolysis over oxidative phosphorylation, even in the presence of oxygen. This metabolic shift supports the rapid proliferation of cancer cells and their survival in hypoxic conditions. Additionally, cancer cells produce abnormal proteins that contribute to tumor progression, such as mutant p53, and fail to produce critical tumor suppressor proteins like RB1, leading to unchecked cell division and evasion of apoptosis. Furthermore, the thesis reviews the role of oncogenes and tumor suppressor genes in cancer development, highlighting how mutations and epigenetic alterations drive the transformation of normal cells into malignant ones. The complex interplay between these genetic changes and the tumor microenvironment is also discussed, emphasizing the importance of signaling pathways, immune evasion, and angiogenesis in cancer progression. This detailed review synthesizes current research and insights from authoritative sources, including peer-reviewed journals and foundational medical texts, to provide a thorough understanding of the physical and biochemical underpinnings of cancer. The findings underscore the importance of continued research in these areas to advance the diagnosis, treatment, and prevention of cancer.

This paper addresses the historically biased selection of problems in technoscience, which has been predominantly shaped by Western male perspectives. We propose a novel framework with objective criteria for identifying and prioritizing human problems worthy of scientific and technological attention. Our approach aims to transcend traditional biases, incorporating a more inclusive, global perspective. We outline metrics considering factors such as scale, urgency, potential impact, and relevance across diverse populations. Using these criteria, we identify key global challenges including climate change, pandemic preparedness, food and water security, education access, sustainable energy transition, AI governance, biodiversity conservation, and mental health. We present a network analysis of their interconnections, revealing complex interdependencies and potential cascading effects of interventions. Our mathematical framework, based on graph theory and network analysis, provides a rigorous foundation for understanding and quantifying these relationships. This research contributes to decolonizing and degendering technoscience, offering a more equitable framework for addressing pressing human problems \cite{roy2018}. Our findings have significant implications for research prioritization, policy-making, and resource allocation in scientific and technological endeavors, potentially reshaping how we approach and address the most critical issues facing humanity.

Mycotoxin contamination of food and feed is a worldwide problem that needed to be addressed with highly efficient and biologically safe techniques. RNA interference (RNAi) is a natural mechanism playing an important role in different processes in eukaryotes, including regulation of gene expression, maintenance of genome stability, protection against viruses and others. Recently, RNAi-based techniques have been widely applied for the purposes of food safety and management of plant diseases, including those caused by mycotoxin-producing fungi. In this review, we summarize the current state-of-art of RNAi-based approaches for reducing aggressiveness of key toxigenic fungal pathogens and mycotoxin contamination of grain and its products. The ways of improving RNAi efficiency for plant protection and future perspectives of this technique, including progress in methods of double-stranded RNA production and its delivery to the target cells are also discussed.

Agriculture is the largest sector of Nepalese economy among the south-Asian developing countries that contributed 26.98 % share of Gross Domestic Product (GDP) in the year 2018/19. The capacity to derive maximum output by per unit of resource is resource use efficiency. Resource use efficiency of a producer explains the comparison between inputs and output value. Potato is staple vegetable in every parts of Nepal. Cobb-Douglas production function is used to predict the significance of inputs in income from cash crops. Due to lack of optimum utilization of available resources in cultivation of vegetable like lack of technical knowledge, low education level, and extensive service the productivity and production is low in Nepalese economy. It ensures vegetable security in Nepal. Though, there are extensive researches on the resource use efficiency and productivity issues on agriculture, very few papers explored in the case of Sudurpaschim province of Nepal OBJECTIVE: This study had the specific purposes: (1) To identify the factors affecting in resource use efficiency and productivity of potato production (2) to utilize the resource use efficiency and productivity in potato production and (3) to show the type of returns to scale in potato production. METHODS: Applying post-positivist paradigm and quantitative causal survey research design, it explored the resource use efficiency and productivity through the semi-structured questionnaire from 140 households by random sampling. Data analysis was carried out by multiple regression model using Cobb-Douglas production function. SPSS software was used to find quantitative results. From the analysis of data using mean, and SD, t-test, analysis of variance, Durbin-Waston test, Marginal Value Product and marginal Factor cost, findings of this research was emerged. RESULTS AND DISCUSSION: The major findings: education level, extension service, farm size and pesticide cost were significant variables in potato production; seed, hired labor, Family Yard Manure and pesticide cost were overused and needed to decrease their cost for optimum allocation and there was decreasing returns to scale in production. This study emphasized on increasing education level, extensive service and farm size for optimum utilization of resources and increasing returns to scale. SIGNIFICANCE: Barriers to Indian potatoes and increasing returns to scale are only possible through protection policy of government. For optimum use of resources and increasing returns to scale, government can introduce capital intensive technique. This study can be implied in policy making and improving existing situation of agriculture, and allocating budget.

The topic of predictive toxicology has been greatly influenced by recent progress in comprehending drug toxicity processes and enhancing medication development. The integration of omics technologies, such as transcriptomics, proteomics, and metabolomics, with traditional toxicological assessments has yielded extensive knowledge about the biological pathways implicated in drug-induced toxicity. The utilization of a multi-omics method amplifies the ability to identify biomarkers that can detect toxicity at an early stage, hence enhancing the safety profile of novel therapeutic medicines. Machine learning and in silico models, such as QSAR models and multi-task deep learning algorithms, have become essential tools. They have shown great accuracy in predicting toxicity endpoints and have helped in the identification of new biomarkers and therapeutic targets. The introduction of microphysiological systems and PBPK modeling has enhanced the transfer of preclinical discoveries to clinical results, providing more precise forecasts of human reactions to medications. Notwithstanding these progressions, obstacles such as the diversity of data and the complex nature of omics data require sophisticated computational techniques for efficient analysis. Continued cooperation and established procedures are crucial to fully utilize these technologies, guaranteeing the creation of safer and more efficient medicinal agents.

Effective leadership is reflected by evidence-based attributes, competencies, and behaviors. The Future of Nursing Report (2011) identified a gap in leadership knowledge, recommending development of creative and innovative strategies to strengthen nursing leadership curricula. These results provided an impetus and charge for nursing education to reexamine and revise leadership content. This mixed methods study analyzed baccalaureate and masters nursing students’ development of their leadership knowledge and skills. Through reflections, undergraduate (n=60) and master’s (n=52) students identified their perceived priorities and tips for success for nursing leaders across the healthcare continuum. Qualitative content analysis aligned students’ comments with the American Organization for Nursing Leadership (AONL) Nurse Executive Competencies (2015). Descriptive data provided the summaries of which leadership competencies were represented. Alignment to the competencies varied, commensurate with the level of educational program: BSN-level management skills vs. MS-level executive skills. Common responses across both programs prioritized communication, professionalism, and leadership behaviors. The results provide an opportunity for students’ synthesis of leadership skills and practices, may guide educators in the design of multi-level leadership curricula, and support development of clinical leaders in practice. This study was prospectively registered with the Campus Institutional Review Board on January 23, 2023, protocol code: 0086-001.

The water exit problem, which is ubiquitous in ocean engineering, is one of the significant research topics in the interaction between navigators and water. The study of the water exit problem can help to improve the structure design for marine ships and underwater weapons for better strength and movement status. However, the water exit problem involves complex processes such as gas-liquid-solid three-phase coupling, cavitation, water separation, liquid surface deformation and fragmentation, making it challenging to study. According to the works carried out by many researchers towards this issue, we summarize the recent developments from three aspects, i.e. theoretical research, numerical simulation and experimental results. In theoretical research, the improved von Kaman model and linearized water exit model are introduced. Several classical experimental devices, data acquisition means and cavitation are introduced in experimental development. Three methods, namely, BEM(boundary element method), FVM(finite volume method) and LES(large eddy simulation) are concluded for numerical simulation. The limitations and shortcomings of these three aspects are then analyzed. Finally, an outlook on the future research improvements and developments of the water exit problem is provided.

The investigation of exoplanetary habitability is integral to advancing our knowledge of extraterrestrial life potential and detailing the environmental conditions of distant worlds. In this analysis, we explore the properties of exoplanets situated with respect to circumstellar habitable zones by implementing a sophisticated filtering methodology on data from the NASA Exoplanet Archive. This research encompasses a thorough examination of 5,595 confirmed exoplanets listed in the Archive as of March 10th, 2024, systematically evaluated according to their calculated surface temperatures and stellar classifications of their host stars, taking into account the biases implicit in the methodologies used for their discovery. Our findings elucidate distinctive patterns in exoplanetary attributes, which are significantly shaped by the spectral classifications and mass of the host stars. The insights garnered from our study not only enhance the existing models for managing burgeoning exoplanetary datasets, but also lay foundational groundwork for future explorations into the dynamic relationships between exoplanets and their stellar environments.

The neural system has limited resources to interact with the environment, and this is where attention comes into play. Attention is a complex process that provides numerous benefits, but there has been a longstanding debate about the mechanisms involved in attentional orientation. Two widely proposed mechanisms are top-down and bottom-up, which relate to the organism's current behavioral goal and the salience of environmental stimuli, respectively. However, distinguishing between these mechanisms can be challenging in both behavioral and neural studies. This review introduces a new conceptualization in which both top-down and bottom-up mechanisms are viewed as aspects of the same process. This unified approach aims to prepare the organism to face stimuli and events based on its prior experiences, immediate (the current task that he/she is aware of), and innate (to be alive) demands.

Triple-negative breast cancer (TNBC) lacks the expression of estrogen receptors, human epidermal growth factor receptor 2, and progesterone receptors (PR). TNBC has the poorest prognosis among breast cancer subtypes and is more likely to respond to immunotherapy due to its higher expression of PD-L1 and a greater percentage of tumor-infiltrating lymphocytes. Immunotherapy has revolutionized TNBC treatment, especially with the FDA's approval of pembrolizumab (Keytruda) combined with chemotherapy for advanced cases, opening new avenues for treating this deadly disease. Although, immunotherapy can significantly improve patient outcomes in a subset of patients, achieving the desired response rate for all remains an unmet clinical goal. Strategies that improve responses to immune checkpoint blockade, including combining immunotherapy with chemotherapy, molecularly targeted therapy, or radiotherapy may improve response rates and clinical outcomes.  In this review, we provide a short background on TNBC and immunotherapy and explore the different types of immunotherapy strategies that are currently being evaluated in TNBC. Additionally, we review why combination strategies may be beneficial, provide an overview of the combination strategies, and discuss the novel immunotherapeutic opportunities that may be approved in the near future for TNBC.

Paper presents proposition of possible extension of The Standard Model Classification of Particles and Fields in way to include gravitation into it.

Pakistan is an agricultural country, and an exporter of crops in many countries. The crop production is an important factor to earn revenue for the country. But the agriculture of Pakistan is still not revolutionized and no modern system has been deployed commonly. Whereas the farmers face difficulty in growing some crops because those crops needs more care and calculated steps. Moreover the farmers face difficulty at different stages of the crop growth like to check fertility of soil and if the soil is non-fertile then which chemical property is lacking. The objective of this research is to provide digitize the agriculture of Pakistan. An emerging technology IoT and Deep learning based system will be developed. The IoT part contains some devices like sensors,gateways and communication technologies whereas the software part consists of Deep learning models that can make predictions about the fertility of the soil. The motive of this system is to provide best results in term of accuracy. Whereas the dataset used is publicly available on kaggle but it was of non-fertile values, so data augmentation is also performed to generate data for fertile values. We have implemented LSTM,RNN,CNN among them LSTM performed best for the prediction of soil fertility.

One of the most crucial attributes of emulsions is their particle size, which has implication on the stability, rheology as well as sensory properties in different food applications. Homogenization speed is an important parameter that disrupts fat globules into desirable particle sizes. The effect of emulsification composition and homogenization parameters on particle size distribution of palm stearin oil-in-water emulsion was investigated. A palm stearin oil-in-water emulsion was homogenized at different speed (10k-25k rpm) and the particle size distribution was investigated. When the homogenization speed was increased above >10k rpm, the particle size distribution decreased. Increasing concentration of surfactant from 1 wt.% to 3wt.%, in the emulsion showed a decrease in particle size distribution for all homogenisation speed. Oil droplet size could also be minimized by increasing the concentration of sugar in continuous phase.

Tegucigalpa, the capital city of Honduras, has the highest number of landslides recorded in the country. In a previous study, landslides were found to be mainly concentrated in areas with colluvium and residual soils. The present study focused on assessing the physical vulnerability of houses and the risk linked to landslides in these types of soils. As an input for this assessment, the study generated landslide risk vulnerability functions based on empirical data. The study's findings suggest that the estimated Annual Average Losses associated with landslides in this region is USD 7.26 million. Moreover, the study developed a novel approach for the spatial and temporal estimation of landslide hazard probability, which overcomes some of the limitations identified in previous landslide risk assessment studies.