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Background: Artificial tooth movement may compromise the occlusion of complete (or implant-supported complete) over-dentures. This movement can lead to traumatic occlusion that may need to be corrected because the planned harmonious occlusion is lost, mainly when anatomic artificial teeth are utilized. Purpose: The study was conducted to evaluate the effect of the combination of gypsum plaster and laboratory silicon on the artificial teeth movement during the flasking procedure using radiographic imaging of intra-flask changes. Methods: In the current study, 90 identical mandibular complete dentures were fabricated and divided into two groups according to the acrylic material used. Stainless-steel pieces (0.5×0.5) were placed in the (buccal and mesiobuccal) cusp tips of the first premolar and first molar on both sides. Each group was subdivided into three subgroups (n=15) representing different techniques of flasking. Radiographs were taken at three phases of the flasking procedure, before and after the second investment layer and after curing the acrylic. The anteroposterior and mediolateral factors were calculated, and the data were analyzed by the one-way analysis of variance (ANOVA) and Duncan’s post hoc tests at P˂0.05. Results: The anteroposterior factors of the groups had insignificant differences at all phases, and the mediolateral factors showed significant differences in the gypsum samples and total silicon samples. Conclusion: Anteroposterior movement of the artificial teeth was not changed due to bracing between the teeth, and a mixed silicon and plaster investing layer had the smallest teeth location changes during the packing and curing phases.

Background: Dairy products are considered some important sources of various nutritional compounds; however, pathogenic bacterial growth is a critical destructive factor to these products leading to consumer health and system financial crises. Aim: The current study was carried out to identify if there is any presence of Staphylococcus aureus related enterotoxin genes in cheese samples. Methods: The research included the collection of 35 samples. The samples passed through conventional cultivation processes and a PCR method to detect the presence of icaA, sea, hla, and fnbA enterotoxin genes in these samples. Results: The conventional identification revealed the growth of S. aureus from the cheese samples. The PCR findings recorded the presence of the icaA, sea, hla, and fnbA in 31 (88.5%), 27 (77%), 19 (54%), and 12 (34%), respectively, of cheese samples. The sequencing revealed close similarities with global isolates, which reached up to 98.5% of identity. Conclusion: The current results indicate the presence of enterotoxin genes of Staphylococcus aureus in high rates in the dairy products examined, which reveals critical problems of food safety due to the possible presence of enterotoxins in consumer dairy products. [Open Vet J 2024; 14(8.000): 2073-2078]

Background: The problem of using psychotropic substances and addiction has become one of the major problems in the world. Despite the significant increase in treatment programs of addiction, many studies indicate that the rate of relapse globally is very high, especially when treatment is limited to the medical side only. Aims: The study aims to determine the percentage of influence of psychological, societal, social, economic, and other factors that lead to relapse when recovering from addiction. Methods: This study conducted in two main hospitals for the treatment of substance use disorders in Baghdad (Ibn Rushud Teaching Hospital for Psychiatry and Al-Ataa Center for Addiction Treatment) through the period from January 10, 2023, to June 10, 2023. All (300 inpatient) who are suffering from relapse to addiction after recovery were included in the study. The scale was prepared for the psychological, social, therapeutic, environmental, and economic factors, which was used by a group of senior doctors working in the field of treatment of addiction and rehabilitation centers, who unanimously agreed with their expertise on these factors. Results: This study revealed that the most important factor for relapse is the availability of addictive substances (91%); other factors include psychological, social pressures that the addict is exposed to in his social environment, in addition to the loss of social support (76%). The pressure of friends or peers with a rate of (78%) and the weakness of family control (44%) in addition to the influence of other factors that were examined in this study. Conclusion: There are many factors affecting the return of those recovering from addiction to addiction again, and the most prominent of these factors is the abundance or ease of access to psychoactive substances in addition to other factors, which include (psychological, social, societal, and economic factors). Society must realize that the responsibility for preventing addiction should not be borne by the medical treatment alone, because it is a problem that must be dealt with collectively by all parties to enable recovered patients from addiction to build their lives with confidence.

Background: Food safety and food-borne infections are major subjects with global interest. Dairy products are considered as important sources for these infections. Aim: The present study was conducted to identify the occurrence and to genotype isolates of Staphylococcus spp. recovered from milk samples in Al-Diwaniyah City, Iraq. Methods: The current study included the collection of 50 milk samples purchased from local stores in the current city. These samples were subjected to bacterial cultivation and biochemical tests. Later, the growth was used to extract the genomic DNA that was exposed to PCR and partial gene sequencing that both targeted the 16S rRNA gene at a specific genetic piece. Results: The PCR results demonstrated the amplification of the genetic fragment of five genetic clusters for each of S. aureus (SAD11, SAD12, SAD13, SAD14 and SAD15), S. epidermidis (SED1, SED2, SED3, SED4 and SED5), and S.intermedius (SID1, SID2, SID3, SID4 and SID5). The PCR products were sent out to sequencing and reported that the current isolates were similar in their genetic content with global isolates at 95.34% to 97.59%, 96.21% to 97.57%, and 96.09% to 97.88%, respectively, of identity. Conclusion: The present findings show highly genetic variations among isolates of S. aureus, S. epidermidis, and S.intermedius recovered from milk samples, and these genotypes are found in different infection setting related to humans and animals, which may pose high risks to the humans and animals. [Open Vet J 2024; 14(7.000): 1689-1700]

The effective and consistent operation of wastewater treatment plant systems (WWTPs) is crucial for the sustainability of the environment and public health protection. The main objective of the present study is concentrated on assessing the reliability of the Karbala wastewater treatment plant’s (WWTP’s) performance. It investigates the plant’s efficiency through the weekly concentration values of three key water quality indicators, which are biochemical oxygen demand (BOD), total suspended solids (TSS), and chemical oxygen demand (COD) collected over 4 years of operation from 2020 to 2023. The methods employed were the coefficient of reliability (COR) method for plant performance in removing the effluent concentrations of 5-day biochemical oxygen demand, COD, and TSS. The analysis found that the COR values were generally close to 1 for all years, with the lowest value recorded at 0.71 in 2020, during the initial stabilization phase of the WWTP. The main finding was that the Karbala WWTP has been effective in pollutant removal. The present study is important because it supplies dependable data that wastewater treatment operators can use to assess their daily operations and gauge the success of biological treatment methods. It is worth noting that no study has been done on the reliability model for examining the quality of wastewater of the Karbala WWTP, and such a method of analysis is considered a new improvement for the evaluation of the plant to meet the Iraqi standards.

Background There is no doubt that vaccination is crucial for preventing the spread of diseases; however, not every vaccine is perfect or will work for everyone. The main objective of this work is to predict which vaccine will be most effective for a candidate without causing severe adverse reactions and to categorize a patient as potentially at high risk of death from the COVID-19 vaccine. Methods A comprehensive analysis was conducted using a dataset on COVID-19 vaccine adverse reactions, exploring binary and multiclass classification scenarios. Ensemble models, including Random Forest, Decision Tree, Light Gradient Boosting, and extreme gradient boosting algorithm, were utilized to achieve accurate predictions. Class balancing techniques like SMOTE, TOMEK_LINK, and SMOTETOMEK were incorporated to enhance model performance. Results The study revealed that pre-existing conditions such as diabetes, hypertension, heart disease, history of allergies, prior vaccinations, other medications, age, and gender were crucial factors associated with poor outcomes. Moreover, using medical history, the ensemble learning classifiers achieved accuracy scores ranging from 75% to 87% in predicting the vaccine type and mortality possibility. The Random Forest model emerged as the best prediction model, while the implementation of the SMOTE and SMOTETOMEK methods generally improved model performance. Conclusion The random forest model emerges as the top recommendation for machine learning tasks that require high accuracy and resilience. Moreover, the findings highlight the critical role of medical history in optimizing vaccine outcomes and minimizing adverse reactions.

In this review, we discuss the use of organic nanoparticles such as liposomes, polymeric nanoparticles, dendrimers, and inorganic nanoparticles such as gold nanoparticles and mesoporous silica nanoparticles in drug delivery in chemotherapy for cancer therapy. Another strategy is the use of nanoparticle vehicles for drug delivery through the natural openings on tumor vessels called fenestrations. Both of these can be functionalized to attach angiotensin to lymphocytes or any certain part of the cancer cell membrane, microenvironment, or cytoplasmic or nuclear receptor sites, and therefore a high concentration of drug delivery to targeted cancer cells is achieved, but with less or no toxicity to normal tissue. The potential advantages evident in this technology are useful approaches to established high-concentration drug treatment of cancer tissues without harming normal cells. Some features of a nanoparticle-based drug delivery system include the durability of the vehicle, biocompatibility, permeation, and ability to target specific types of cells. Organic and inorganic nanoparticles have developed this kind of drug-carrier system. Particulate systems are also still being explored for cancer drug resistance mechanisms, and their function in immunotherapy is expanding.

Free Space Optics (FSO) is a potential optical technique poised to complement traditional wireless communication. Using optical signals for point-to-point transmission, FSO offers advantages such as abundant unregulated bandwidth, high data rates, enhanced security, and lower costs than microwave links. However, attenuation due to weather conditions, particularly rain, poses a significant challenge to both FSO and RF transmission. This study proposes a Hybrid FSO/58GHz system model to address rain-induced attenuation, implementing the ITU-R FSO prediction model in Kuala Lumpur to evaluate performance in Malaysia. Utilising three years of rain intensity data from UTM, Kuala Lumpur, the study computes rain attenuation for an FSO link with a 780 nm wavelength based on the ITU-R P.1814 model. Specific attenuations for various RF frequencies are also estimated to identify a suitable frequency for the hybrid system. The study analyses the impacts of channel attenuations on both FSO and RF links to enhance system availability and data rate. Key performance metrics such as received power (Pr), signal-to-noise ratio (SNR), and bit error rate (BER) are assessed for a 1 km link. The results demonstrate the successful implementation of the FSO link based on the ITU-R model in Malaysia, identifying 58GHz as the optimal RF frequency for the hybrid system and improving performance under heavy rain conditions.

Printed electronics, fueled by graphene's conductivity and flexibility, are revolutionizing wearable technology, surpassing copper's limitations in cost, signal quality, size, and environmental impact. Graphene-based inks are positioned to lead in this domain, offering cost-effective solutions directly applicable to materials such as textiles and paper. However, graphene encounters a primary drawback due to its lack of an energy band gap, constraining its potential applications in various electronic devices. In this study, we present a novel formulation of a superconductive, flexible leather graphene antenna utilizing a tri-nanocomposite structure of Graphene Nanoplatelet/Silver/Copper (GNP/Ag/Cu), covering a wideband bandwidth from 5.2 GHz to 8.5 GHz. The electrical conductivity of the GNP/Ag/Cu sample was assessed using the four-point probe method. With each additional layer, conductivity increased from 10.473 × 107 S/m to 40.218 × 107 S/m, demonstrating a direct correlation between conductivity and antenna gain. The study evaluates the efficacy of various thicknesses of conductive Graphene (GNP/Ag/Cu) ink on drill fabric. Safety assurance is provided through specific absorption rate (SAR) testing, indicating 0.84 W/kg per 10 g of tissue for an input power of 0.5 W, in compliance with ICNIRP standards for wearable device safety. Additionally, a morphological analysis of the antenna was conducted, showcasing its potential for efficient signal transmission in wearable electronic devices.

Background and Objectives: Herpes zoster, or shingles, is caused by the varicella-zoster virus (VZV), which initially presents as chickenpox in children. VZV is a global health concern, especially in winter and spring, affecting 10-20% of adults over 50 and posing a 30% risk for the general population. This study used PCR to detect VZV, confirming results with duplicated DNA samples and identifying 234 bp fragments by targeting the gpB gene. Materials and Methods: This study examined 50 herpes zoster cases from October 2020 to April 2021, involving 30 males and 20 females aged 10 to 90, diagnosed by dermatologists. Data were collected via a questionnaire. PCR detected VZV by amplifying the gpB and MCP genes from skin lesion samples. Six positive 234-bp PCR products were sequenced at Macrogen Inc. in Seoul, South Korea. Results: Six DNA samples with 234 bp amplicons were sequenced, showing 99-100% similarity to human alpha herpesvirus sequences in the gpB gene. NCBI BLAST matched these sequences to a reference (GenBank acc. MT370830.1), assigning accession numbers LC642111, LC642112, and LC642113. Eight nucleic acid substitutions caused amino acid changes in the gpB protein: isoleucine to threonine, serine to isoleucine, and threonine to Proline. These variants were deposited in NCBI GenBank as gpB3 samples. Conclusion: The study found high sequence similarity to known VZV sequences, identifying six nucleic acid variations and eight SNPs. Notable amino acid changes in the gpB protein were deposited in NCBI GenBank as the gpB3 sample.

Background There is no doubt that vaccination is crucial for preventing the spread of diseases; however, not every vaccine is perfect or will work for everyone. The main objective of this work is to predict which vaccine will be most effective for a candidate without causing severe adverse reactions and to categorize a patient as potentially at high risk of death from the COVID-19 vaccine. Methods A comprehensive analysis was conducted using a dataset on COVID-19 vaccine adverse reactions, exploring binary and multiclass classification scenarios. Ensemble models, including Random Forest, Decision Tree, Light Gradient Boosting, and extreme gradient boosting algorithm, were utilized to achieve accurate predictions. Class balancing techniques like SMOTE, TOMEK_LINK, and SMOTETOMEK were incorporated to enhance model performance. Results The study revealed that pre-existing conditions such as diabetes, hypertension, heart disease, history of allergies, prior vaccinations, other medications, age, and gender were crucial factors associated with poor outcomes. Moreover, using medical history, the ensemble learning classifiers achieved accuracy scores ranging from 75% to 87% in predicting the vaccine type and mortality possibility. The Random Forest model emerged as the best prediction model, while the implementation of the SMOTE and SMOTETOMEK methods generally improved model performance. Conclusion The random forest model emerges as the top recommendation for machine learning tasks that require high accuracy and resilience. Moreover, the findings highlight the critical role of medical history in optimizing vaccine outcomes and minimizing adverse reactions.

The increase in bacterial infections and the emergence of antibiotic resistance has led to the development of bio-derived and environmentally friendly nanomaterials to counteract bacterial activity, and silver nanoparticles AgNPs are a promising way to achieve this. The present work aimed to synthesize AgNPs from the blue-green algae Athrospira Platensis and evaluate their antibacterial efficacy against Enterococcus faecalis, Staphylococcus aureus, Proteus mirabilis, and Pseudomonas aeruginosa isolated from human urinary tract infections. The results were shown and confirmed by peak UV spectra at 450. Through SEM and DLS analyses, the shapes of the AgNPs were determined to be spherical and with sizes ranging from 15 to 100 nm. The zeta potential values of AgNPs were found to be −20 ± 3.2 mV indicating the absence of AgNPs aggregates. Synthetic AgNPs produced by A. platensis showed a strong antibacterial effect against bacteria isolated from human urinary tract infections. The diameters of the inhibitory zone for S. aureus E. faecalis P. mirabilis and P. aeruginosa 14 mm, 16 mm, 15 mm, and 12 mm, respectively. AgNPs showed the highest activity against E. faecalis strain, with the diameter of the inhibitory zone reaching 16 ± 0.2 mm at a concentration of 800 μg/mL.These results will be a useful resource for studying the effects of man-made nanoparticles on the environmental safety and represent a promising step toward realizing AgNP-based antimicrobial drug production.

Background. Increased FOXP3+ Treg levels in the TME were positively correlated with a worse prognosis in certain cancer patients. FOXP3 was significantly overexpressed in pediatric B-ALL patients, and this overexpression was associated with a worse prognosis and increased risk of disease relapse. It is unknown if children that have the condition would have different prenatal immune development. This study investigates the relationship between IL10, and immunological development in pediatric ALL. Methods. The 70 blood samples from children between the ages of 2 and 14 for both sexes were obtained from patients with Acute lymphoblastic leukemia. Furthermore, this study comprised 54 healthy controls. Included in this study, FOXP3 expression on leukemic blast cells were assessed using flow cytometry. And IL10 were assessed using ELISA test. Results. Increase of FOXP3 cells was noticed in children with ALL compared to healthy individuals with significant increase of FOXP3 (mean ± SD, 91.156 ± 12.255 vs. 14.88 ± 7.897pg/ml (p

Recently, the technology of Underwater computer vision has played a vital role by improving the quality of underwater images owing to its significance in different applications in marines, such as military, resource development, biological research, and underwater environmental assessments. Moreover, light is absorbed and scattered while propagating through water, leading to color distortion. Additionally, floating micro-particles in the water contribute to low image contrast, resulting in blurry and poorly lit underwater images with a color cast. Therefore, many researchers have been attracted to developing diverse computer vision-based methods to improve the quality of underwater images, such as restoration, enhancement, and deep-learning techniques to restore and enhance degraded underwater images. Although numerous studies have attempted to address these issues, there is still much room for improvement in the quality of the produced images. To this end, this paper proposes a new enhancement method to improve underwater image quality. The presented approach utilizes the Coronavirus herd immunity optimizer algorithm for underwater image enhancement (CHIO-UIE) and is evaluated using standard measures on public datasets. The empirical results demonstrate that the CHIO-UIE method enhances the quality of images based on qualitative and quantitative evaluations, successfully improving underwater images with low contrast and light by significantly enhancing the visual impact of distorted underwater images across various underwater environments.

Livedoid vasculopathy (LV) is a chronic, recurrent thrombotic vasculopathy characterized by painful ulcerations on the lower extremities, which heal slowly and leave atrophic white scars known as “atrophie blanche.” This report presents the case of a 31-year-old woman with a 4-year history of recurrent painful ulcerations on her legs and feet. A skin biopsy revealed findings consistent with LV, and an exhaustive laboratory workup ruled out secondary causes such as thrombophilia, malignancies, autoimmune diseases, and peripheral arterial disease. The patient showed remarkable improvement with a treatment regimen of pentoxifylline, nifedipine, and warfarin, resulting in complete ulcer resolution and sustained remission over 5 months. Our case highlights the importance of a comprehensive diagnostic approach and a multidisciplinary treatment strategy in managing primary LV to achieve remission and prevent recurrence of skin ulcerations.

Background: Obesity and major depression disorder are two of the most common diseases in the world. They are also big problems because they have a very strong effect on people's health and well-being, but also because of their high morbidity and mortality rates and socioeconomic effect. Aim of the study: This study to study the association between obesity and depression, and to explore the link between body mass index and socio-demographic characteristics. Patients and methods: A case-control study utilized a random sample of 300 subjects (100 obese group and 200 normal weight group) attending diabetes and endocrinology center at Al- Najaf province. All subjects have been taken randomly from adult individuals with age range between (18-60) years in Al-Najaf province. The data were collected from October to the February. The obtained data analyzed by Version 28 of the Statistical Package for the Social Sciences (SPSS). Results: The current study found a significant association between obesity and depression, indicates that those with moderate/severe depression scores are more likely to be obese than those with mild depression or no depression (odds ratio = 2.306 times, 95% CI: 1.360-3.910). With (p = 0.002). The relationship between obesity and socio-demographic factors, this study found positive association between obesity and exercise (p = 0.001) and family history of obesity (p = 0.037), while the other characteristics were not significant. Conclusions: The current study concluded that those who had moderate or severe depression symptoms were more likely for developing obesity than those who had a mild or no depression symptoms.

The purpose of this paper examination the sustainability reporting (SR) and corporate profitability (CP) of the south Asian large banks. This research employs the secondary data from 134 banks for the year 2019–2022. The results of this paper display that there is a positively and significantly relationship among SR and its dimensions (community and environment) with CP. The most important issues of sustainability in banks and companies do not disclose information related to the environment and society that will effect negatively on the institutions reputation. For the researchers’ best knowledge, this research creates important support in terms of SR in south Asian large banks. In addition to this study propose the sustainability improves banks and firm’s reputation and interests customers and investors involved in sustainable problems.

The lower olefins (Ethylene, propylene, and butylene) are considered the key to the polymeric and petrochemical industries. Dehydration of alcohols to produce light olefins (Methanol-to-olefins reaction) over SAPO-34 molecular sieve has attractedintoigh attention. Modified SAPO-34 zeolite catalyst with Zr metal was successfully prepared under microwave irradiation using morpholine as a structure direct agent. The microwave energy power used was 800 w and the crystallization time was 200 min. The catalyst sample was characterized by XRD, SEM, EDX, BET, FTIR, and TGA analysis. XRD analysis exhibited a typical chabazite structure with high crystallinity. The analysis showed macrocrystalline particles with moderate distribution of silica in the framework structure and a low surface area of 77 m2/g. The vibration peaks of the prepared catalyst showed agreement with the SAPO-34 CHA structure. Catalyst performance towards methanol-to-olefins conversion was performed in a trickle bed reactor with temperatures of 350, 400, 450, and 500 oC at a weight hourly space velocity of 7.7 h-1. The results also reveal at a temperature of 400 oC , that the best olefins selectivity was obtained, reaching 70%, with a longer lifetime of 500 min. methanol conversion was almost 100% at all reaction temperatures. In addition, the effect of methanol concentration was investigated and the results showed that increasing of water content plays a role in increasing catalyst lifetime and preventing coke depositions in pores.

The Tigris River is the primary source of water for human consumption in Iraq and is the ultimate sink for wastewater generated by activities. This research was conducted between November 2021 and September 2022 using 15 physio-chemical parameters (pH, air and water temperature, EC, salinity, DO, BOD, TH, Ca+, Mg+, SO4, TDS, TSS, turbidity, and Chloride), two heavy metal parameters (Cr, and Al), and biological pollutants to analyze temporal and spatial variation and the effects of pollutants sources on the water quality of the Tigris River from the north to the south of Baghdad city. The results show that some values of the tested parameters were higher than Iraqi and WHO standards for the water river, which call for attention to be paid to the load of pollutants entering the river to avoid risks and future problems. On the other hand, the results presented indicate that biological pollution has been diagnosed at the three southern stations (Shuhada'a Bridge, Al-Za'afarania, and Jisr Diyala) with all the types of bacteria in the four seasons, which indicates that increasing the fecal contamination in the middle and southern sampling stations is due to increasing the wastewater discharge into the river body.

Applications of microalgae in environmental studies have recently increased. Current uses of immobilized microalga Chlorella vulgaris include reducing pharmaceutical substances such as amoxicillin AMX and potassium dichromate K2Cr2O7 on freshwater clam Pseudodontopsis euphraticus as a biotic model. Recent research pointed out a change in biomarkers of oxidative stress in an evaluation of induced toxicity. Where clams were exposed to different concentrations100, 200, and 400 mg/L for 7 days and 20, 30, and 50 mg/L for 5 days of amoxicillin and potassium dichromate, respectively. The results showed that exposure to AMX and K2Cr2O7 led to a significant change in the activity of antioxidant enzymes, with significant increases (p

Background: Food safety is an important subject that global cheese industry increases the awareness upon. This urges these economic sectors to elevate the level of research to minimize cheese contamination with pathogenic bacteria, such as Salmonella. Aim: Based on these merits, this study was conducted to genotype Salmonella spp isolated from cheese samples of local stores in Al-Diwaniyah City, Iraq. Methods: The study used 41 samples of local fresh unsalted white cheese in a selective-growth based isolation of Salmonella. These isolates were confirmed utilizing a slide-agglutination (SA) test and VITEK® 2 system (V2S). Then, the isolates were subjected to conventional PCR and sequencing techniques that both targeted the 16S rRNA gene. For subtyping, the Salmonella isolates were subjected to a random amplified polymorphic DNA (RAPD)-PCR method. Results: The results of both SA and V2S revealed the presence of 14 (34.2%) isolates of Salmonella spp. in the cheese samples. The PCR confirmed 6 (42.9%) of these isolates, which further were defined with close nucleotide similarity (98.03%) and (97.88%) to different world isolates, such as Salmonella enterica subsp. Arizonae and Salmonella enterica subsp. enterica serovar Typhi, respectively. The RAPD-PCR findings showed different fragments for all the tested isolates. Conclusion: The present study indicates that the samples of the local fresh unsalted white cheese contain different Salmonella genotypes, which could be originated from different contamination sources. [Open Vet J 2023; 13(10.000): 1277-1282]

The purpose of this research is to present a new model for the nonlocal reductions of the multi-component discrete Manakov system. In particular, the focusing solution is determined based on a special condition of the potential function. This study includes: solving the spectral problem and finding the eigenfunctions and the scattering data. The importance of our study lies in examining the conditions distinguishing the solution called a soliton. There are two cases of the potential functions: single and double excitations, if the Lax operator has no spectrum neither outside nor inside the unit circle then, there is no soliton solution, this happens with a single site case. On the other hand, the two-site case gives two soliton solutions. It is shown that the soliton is more likely to occur at the discrete eigenvalues outside or inside the unit circle, as the excitations are more than one. Each case introduced is supported by numerical simulations.

Recently, magnetic solid-phase extraction (MSPE) is an important technology due to its use in analytical chemistry, biotechnology, and medicinal fields. MSPE shows rapid isolation of target analyte from large volume samples, the huge surface area of magnetic nanoparticles (MNPs), and simplicity in application due to using an external magnetic field instead of using packing column, centrifuge and filter papers. The aim of this review is to evaluate the extraction and determination of dyes in food and water samples by using the MSPE technique.

In recent years, global pharmaceutical consumption has increased, resulting in the increased release into the environment and endangering the entire ecosystem. These pharmaceuticals have attracted considerable attention due to their persistence, toxicity, and the appearance of resistance genes and development antibiotic-resistance bacteria. Furthermore, conventional wastewater treatment plants are ineffective in treating antibiotic-contaminated wastewater.Thus, algae-based technologies are sustainable, low-cost, and friendly to the environment. In this context, immobilization appears to be of particular interest to many researchers as they develop new, efficient, greener strategies for the elimination of toxic and hazardous pollutants. provide a critical overview of algal immobilization-based technologies, and a biotechnological tool that restricts cell movement by confining it within a polymer matrix or attaching it to a rigid support is a promising ,and cost-effective alternative that does not necessitate the use of additional chemicals. This paper presents strategies for the systematic removal of pharmaceuticals based on algae immobilization techniques as an economical, effective, and feasible alternative technology for removing pharmaceuticals and environmental concerns from water bodies and discusses the benefits and drawbacks of these techniques

The key natural cause of irradiation in humans is the air. People spend most of their time at home, so home is likely a main source of natural radionuclide exposure in the air, especially radon gas. It is the second cause of lung cancer after smoking. This study aims to evaluate Radon-222 gas (222Rn) concentrations in the houses (indoor dwellings) of the Al-Hussainya district of the Karbala Governorate, Iraq. Also, some radiological parameters such as AED (annual effective dose), PAEC (potential alpha energy concentration), EP (exposure to radon progeny), and CPPP (lung cancer cases per year per million people) were calculated. 222Rn concentrations were determined using closed and open dosimeters with CN-85 detector (thickness of 12 μm). The range and average of 222Rn concentrations were from 21.791 Bq/m3 to 43.376 Bq/m3 and 32.3381 Bq/m3 in open dosimeters, respectively. While in closed dosimeters, the range of 222Rn concentrations and average values were from 19.324 Bq/m3 to 37.286 Bq/m3 and 26.6462 Bq/m3, respectively. The average values of AED, PAEC, EP, and CPPP due to radon by open dosimeters were 0.083 mSv/y, 0.358 mWL, 14.759 mWLMY−1, and 1.503, respectively, while the average values of AED, PAEC, EP, and CPPP due to radon by closed dosimeters were 0.063 mSv/y, 0.270 mWL, 11.134 mWLMY−1, and 1.134, respectively. According to WHO, EPA, and ICRP, the values of radon concentrations were within the range of what was allowed internationally. Also, the results of the radiological parameters due to radon gas for the study of the houses of the Al-Hussainya district of the Karbala Governorate, Iraq, were low and did not constitute a health hazard.

Background. Type 2 diabetes is a condition in which the body becomes resistant to the effects of insulin, leading to reduced insulin production in the pancreas. It has genetic- and family-related risk factors that cannot be changed, along with modifiable lifestyle factors. The precise genetic causes of type 2 diabetes are still unknown. However, individuals can potentially slow or stop the progression of the condition by making dietary adjustments and increasing physical activity levels. Material and Methods. Forty-five type II diabetic patients in the study included participants between 40 and 60 years old, with a minimum duration of one year, as well as 45 healthy control subjects who were matched in terms of age and sex, and had no underlying systemic diseases. Oral examination is done for the symptoms including burning sensation, candidiasis, and a reduction in the production of saliva. The rate of saliva flow (in milliliters per minute) was measured in samples of saliva that were not stimulated. The salivary trace elements and levels of adipocytokines were evaluated using colorimetric and Ethylenediaminetetraacetic acid (ELISA) testing. The quantification of Candida colony numbers, an enrichment and culture approach, was used to achieve a concentration of 100,000 colony-forming units per milliliter (CFU/ml). The ShowNovo WG1 halimeter was used to measure volatile sulfur compounds in breath. The salivary glucose oxidase assay was conducted using a colorimetric technique, while the determination of trace elements was also performed using a colorimetric assay method. Result. The diabetic group exhibited a significant increase in the number of Candida spp colonies due to elevated levels of glucose in the saliva (p>0.05). However, the variables being examined, such as body mass index (BMI), burning mouth syndrome (BMS), salivary flow rate (SFR), salivary leptin, salivary copper, and salivary magnesium, did not exhibit any significant variations in quantities between the diabetic and healthy groups (p>0.05). Conclusion. The data collected in this research aid in the creation of a preventative program for oral fungal infections in individuals with type 2 diabetes. The program utilizes saliva and its constituents.

Background: A cross-sectional survey was conducted at the period from 1st of January to 31st of March 2015 in Babil governorate-Iraq. A systematic random sampling technique was used to collect 420 patients from 8 main primary health care centers chosen randomly. They consented to interview directly by the researcher using questionnaire Of the 420 patients, 168 (40%) were obese. The body mass index classes had a statistical significant association with ; age, occupation, residence (P=0.000). Eating: sweet, chocolate (P=0.000); fruit (P= 0.001); skipping breakfast (P=0.027); TV watching time (P=0.004); moderate activity frequency and time consumed (P=0.000), sleep duration, family history of obesity (P=0.000). Logistic regression analysis predicted some factors that increased the odds of obesity; age (OR=1.159), no job or retired(OR=10), business (OR=12.6), skipping breakfast (OR=1.46), eating sweet and chocolate (OR=2.709), time of TV watching (OR=3.319), and family history (OR=3.746), whereas some factors decreased the odds like; farmer (OR=0.013), laborer (OR=0.042), rural residence (OR=0.136), eating fruit (OR=0.502), moderate physical activity (OR=0.26) . Conclusions and recommendations: Obesity prevalence was 40%, and associated with socio-demographic features, eating habits, physical activity , sleep duration, and family history. The study recommended adoption of health education programs about obesity by Ministry of Health regarding healthy diet, decrease sedentary lifestyle, encouraging of physical activity at all ages for proper prevention of obesity.

With the rapid growth of high-rise buildings and large-scale structures, there is a need to preserve natural resources and reduce loads on buildings by using lightweight concrete to achieve better performance for structures. In the study, four groups were prepared; the first group included one mix containing natural aggregate, and the second mix replaced all the natural aggregates with lightweight pumice aggregates. These mixes are reinforced with carbon fiber with a 0.5% volume fraction. In the second group, a variable volume fraction of carbon fiber of (0.0 and 1%) of mixes. In the third group, the mixes have different lengths of carbon fiber (20mm, 30mm) and a volume fraction of carbon fibers 0.5%. Finally, the fourth group partially replaces sand as a variable with a percentage of lightweight fine aggregates (10% and 30%) reinforced with fibers. Adding carbon fibers to the concrete specimens by 0.5% and 1% improved splitting tensile strength and flexural strength compared to the specimens containing carbon fibers with a length of 5mm. Also, enhanced samples containing fibers by 0.5% and lengths of 20 mm or 30 mm, compared to the sample containing carbon fibers with a length of 5 mm. Also, the specimens containing lightweight fine aggregates as a replacement with a percentage of sand have a lower splitting tensile strength and flexural strength than the reference mix.

Background: There is no doubt that vaccination is crucial for preventing the spread of diseases; however, not every vaccine is perfect or will work for everyone. The main objective of this work is to predict which vaccine will be most effective for a candidate without causing severe adverse reactions and to categorize a patient as potentially at high risk of death from the COVID-19 vaccine. Methods: A comprehensive analysis was conducted using a dataset on COVID-19 vaccine adverse reactions, exploring binary and multiclass classification scenarios. Ensemble models, including Random Forest, Decision Tree, Light Gradient Boosting, and extreme gradient boosting algorithm, were utilized to achieve accurate predictions. Class balancing techniques like SMOTE, TOMEK_LINK, and SMOTETOMEK were incorporated to enhance model performance. Results: The study revealed that pre-existing conditions such as diabetes, hypertension, heart disease, history of allergies, prior vaccinations, other medications, age, and gender were crucial factors associated with poor outcomes. Moreover, using medical history, the ensemble learning classifiers achieved accuracy scores ranging from 75% to 87% in predicting the vaccine type and mortality possibility. The Random Forest model emerged as the best prediction model, while the implementation of the SMOTE and SMOTETOMEK methods generally improved model performance. Conclusion: The random forest model emerges as the top recommendation for machine learning tasks that require high accuracy and resilience. Moreover, the findings highlight the critical role of medical history in optimizing vaccine outcomes and minimizing adverse reactions.

Background: The additive manufacturing technology made the topology optimization technique feasible. This technique can indefinitely reduce the weight of the printed items with a promising increase in the mechanical properties of that item. Materials and Methods: In the current experimental study, 50 samples were fabricated for a 3-point bending test. They were divided into ( n = 5) as a control Group 1 free of internal geometries, ( n = 15) for each of Groups 2-4, and they were subdivided into ( n = 5) for each percentage of reduction per volume (10%, 15%, and 20%). Spherical, ovoid, and diamond shapes were each group's fundamental geometries, respectively. Cylindrical tunnels connected the voids in each group. Radiographic images were performed to validate the created geometries, the weight was measured, and flexural strength and modulus of elasticity were calculated. Data were analyzed by one-way ANOVA and Duncan's post hoc tests at P