Journal of University of Babylon

Background: The chance of camel thistle squander as eco-accommodating, accessible, and monetary adsorbent for adsorption methylene blue color from its watery arrangement was analyzed by utilizing clump and section framework. All experiments of the batch were achieving with modification camel thorn waste dye concentration 50 mg/L, pH6.5, Temp 25 oC.
Materials and Methods: Camel thorn (CT) waste were collected from AL-Mahaweel region, this region situated in Babylon city/Iraq. The waste were direct washed with running water tap to release all impurities, and rinsed with distilled water for 4 times, after then it dried under sunlight, and then in oven under 50 oC for two hours. The dried (CT) waste were ground and sieved BSS-60 mesh size particle
Results: Methylene Blue(MB) dye was examined to remove from the aqueous solution by adsorption on the camel thorn waste added to the acidic adsorbent modification, thermal adsorbent modification on the decolonization dye efficiency was studies were investigated with the similar working condition contact time (2-90 min).
Conclusion: The current discoveries created the impression that the that normal adsorbent, camel thistle squander is altogether appropriate for the depolarization of methylene blue color from its watery arrangement. The outcomes show that the balance isotherm for the two modules that utilized in this work are of good kind, for being curved vertical

Cancer is one of the great challenges for the patient and his family, often the family or caregivers suffer from psychological burden. Cancer is a devastating disease that necessitates extensive treatment and ongoing support to aid people physically, emotionally, and financially. Therefore, not only does the sufferer but also his loved ones feel the weight of a cancer diagnosis. Family members typically offer care for a loved one with cancer in addition to professional aid, beginning with the initial diagnosis and continuing through recovery or death. Increased survival rates are the result of significant advancements in therapy, and cancer is now more likely to be viewed as a chronic condition requiring care primarily outside of a hospital. They seem to be more likely to get sick and die, which is a sign of a higher risk for death. Caregiver burden is when a caregiver's mental or physical health is at risk or when the amount of care, they have to give is more than they can handle. The load seems to be common among family caregivers, but there are not many ways to help them. There are factors that increase the burden on caregivers and thus make it more difficult for their patient to recover, because caregivers are unable to fully comply with them because of the burden.

The field of evolutionary robotics is an interesting research area that deals with building neuro-controller systems by evolving individuals depending on the Darwinian principles of natural selection and survival of the fittest. It stems its importance from the need of building an intelligent robots that can learn to behave autonomously in unexpected situations in unknown and unpredictable environments.
Materials and Methods:
This paper produces Breeder Genetic Algorithm (BGA) as the tool in an evolutionary mobile robot system. BGAs share aspects with traditional GAs and evolution strategies. The controller is tested in the task of obstacles avoidance. Also the system is tested when two tasks are wanted to be modulated (Homing and obstacle avoidance).
Results:
It is shown that evolution enhances the performance of the system in terms of the average population fitness and the best individual fitness. It is also demonstrated that it is feasible to use several different modules that can cooperate to perform a given task.
Conclusion:
Different runs in the evolutionary systems can produce different solutions. Also, simulations can help making several important decisions concerning the initial parameters governing the evolutionary controller systems. The fitness function must properly be designed to yield the desired behavior. All the experiments exhibit an enhancement in the level of the average population fitness and best individual fitness across generations. Furthermore, the performance of evolved individuals can be evaluated subjectively by observing the trajectories and behavior made by the best controller developed by the BGA.

Background
Pulses increased the thin-film sample preparation was carried out via a laser ablation method. 5 tons of pressure which were used to compress powdered (CZTS) pellet form. Utilizing a Neodymium-YAG laser with a range of 700mJ laser energy, and the plasma plume was created at a pressure of 10-5mbar utilizing at a frequency of 6Hz. Electrical Properties including Hall effect and electrical conductivity were investigated. According to Hall measurements, the films prepared were p-type at 200 pulses and changed to n-type as the number of pulses increased. They also had two activation energies (Ea1 ,Ea2). The conductivity was shown to increase as the number of pulses increased.
Materials and Method
A Neodymium-YAG laser with a range of 700mJ laser energy, and the plasma plume of 10-5mbar were utilizing number of pulses at a frequency of 6Hz. The Hall effect and electrical conductivity were investigated.
Results
Hall effect and D.C were studied. According to the findings, the prepared films were p-type at 200 pulses and changed to n-type as the number of pulses increase. They also had two activation energies (Ea1 and Ea2).The electrical conductivity was shown to increase as the number of pulses.
Conclusions
Two activation energies ( Ea1 , Ea2). Hopping method for moving the carriers between levels inside the energy gap and the thermal stimulation method for moving between other levels. The carrier type of CZTS compound films change from p-type to n-type as the number laser pulses increase.

Background:
The current experimental study presents the effect of silver nanoparticles (Ag NPs) on improving the optical properties of a light-emitting polymer (LEP) based on Plasmon-Exciton Coupling.
Materials and Methods:
A Poly(9,9-di-n-octylfluorenyl-2,7-diyl)(C29H41) polymer (PFO) is one of the light-emitting polymers that has distinctive optical properties when it is dissolved by toluene different concentrations.
Further, the Ag NPs are experimentally synthesized by pulsed laser ablation in liquids technique to be subsequently mixed with the PFO polymer at different concentrations.
Results:
Based on the results, the Plasmon properties possessed by the Ag NPs improved the absorbance and fluorescence spectra of the PFO polymer for all concentrations. In addition, the light-induced fluorescence spectra are improved under the influence of laser beams by adding the Ag NPs to the PFO polymer.
Conclusion:
The current study showed that with increasing the concentration of the Ag NPs in the PFO polymer solution, a red shift appeared in the wavelength of the absorption and fluorescence spectra. This wavelength shift is most likely the result of the strong interaction between the plasmon of the Ag NPs and the exciton of the PFO polymer under the influence of laser light. In turn, this interaction can lead to changes in the energy states of the PFO polymer thus improving its optical properties.

Researchers from all around the world are interested in nanoparticles of zinc oxide (ZnO-NPs) because of their extensive biological functions. In addition to be less toxic and biodegradable, they can dramatically increase pharmacophore biological activity. ZnO-NPs are the most commonly utilized metallic nanoparticle in electronics and optics due to their distinct visual and chemical characteristics, which may be easily altered by modifying the structure and broad bandgap. Repetition their affordability, biocompatibility, and biodegradability, ZnO-NPs are a viable option as a nanocarrier for conventional medications. ZnO NPs' tiny particle size and large surface area can improve surface reactivity by enhancing antibacterial activity. Additionally, as the surface characteristics of nanomaterials modify their interactions with cells, this may prevent ZnO NPs from having their intended antimicrobial effect. Surface modifications covering ZnO NPs can therefore play a role in moderating antimicrobial activity. ZnO NPs' antibacterial activity may be increased by adding surface modifiers containing groups harmful to microorganisms. This article discusses in detail the biopotency of ZnO-NPs in antibacterial, anti-inflammatory, antifungal, antidiabetic, anticancer, antioxidant, and antiviral applications.

Background: Although graph theory plays a significant role in representing the causes of a problem and the relationship between them to facilitate its solution, there are many problems in our real lives that cannot be represented accurately due to the inaccuracy and ambiguity of the available data. In this article, Cayley (SVNG) will define and look into some of its characteristics. In terms of algebraic structures, we demonstrate a few intriguing characteristics of SVNGs. Additionally, planarity in Cayley (SVNG)s will be discussed.
Materials and Methods: The single-valued Neutrosophic sets (SVNS) were used, which depend on three functions from the universal set, say X, to the standard range [0, 1] and emanating from the non-standard range ]-0, 1^+[ which the Neutrosophic sets rely on. The Cayley table of algebraic groups was used.
Result: This article introduced the idea of neutrosophic Cayley graphs (NCG) as a combination of graph theory and algebraic structure, and some of its properties were studied in different environments where the algebraic Cayley structure exists. For example, it was proven that every reflexive and transitive Cayley graph is regular and so on.
Conclusion: It can be concluded that a relationship has been built to draw a weighted directed graph for SVNS that contains three components (truth, indeterminacy, and false). and many interesting features of the neutrosophic graph (NG) were displayed, such as transitivity and regularity. The planarity of Cayley's neutrosophic graph has also been demonstrated, and observations and theorems have been formulated in relation to it.

Multimedia protection has become a significant problem in the society where the intellectual property is threatened. Digital watermarking can be considered as a solution to protect the multimedia. Property protection is a common field of research compared to other fields such as identity verification and local manipulation localization. Imperceptibility and robustness are the most crucial requirements for multimedia watermarking. High distortion is provided by watermarks with high robustness. We must so strike a balance between them. Recently many works based on frequency range which can satisfy watermarking requirements such as high robustness and low distortion. Visual attention based image watermarking is considered one of image watermarking methods due to detect the most important regions for watermark embedding. The lack of robustness against malicious cyber-attacks makes watermarks easily detectable and destroyed. As a result, the proposed watermarking scheme becomes more complex and cannot withstand diversity Geometric and non-geometric attacks. Therefore, there are many existing visual attentions based image watermarks. This paper analyzes the techniques for image watermarking against various types of attacks and presents the applications of digital watermarking.

Loop unrolling is one of the key optimization strategies that compilers employ to enhance the efficiency of loop-based programs. The loop unrolling approach aims to minimize the number of iterations carried out by the loop, hence reducing the sub-instruction overhead. We divide the current state-of-the-art loop-opening strategies into two groups in this survey paper: machine learning-based strategies and conventional strategies.
Several conventional techniques are used in unrolling the loop, such as profile-based, heuristic-based, and static analysis-based techniques. As a result, the amount of instructions, the loop nesting structure, and the number of loops will all be taken into consideration by these approaches when determining whether to unroll the loop. Because these techniques are frequently constrained by their presumptions, they might not always yield the optimal outcomes. In contrast, loop unrolling can anticipate the ideal loop unrolling factor by utilizing machine learning-based techniques such artificial neural networks, k-nearest neighbors, decision trees, support vector machines, and random forests. When these techniques were compared to other conventional techniques, the outcomes were superior.
In this paper, we supply a comprehensive review of the existing loop unrolling techniques, which include their strengths and limitations. Also, we compare the different machine learning-based approaches and debate the potential benefits of using machine learning in loop unrolling optimization. Our goal is to provide a comprehensive overview of the field and to provide guidance for future research in this area.

Background:
The interacting boson model was introduced in 1974 as an attempt to represent the collective features of nuclei in a coherent approach. This model is the fundamental model for explaining nuclear properties. The Bohr and Mottelson collective model was developed from this model to represent quantum mechanical collective motion such as rotations or which called SU(3) and vibrations motion and called U(5).
Materials and Methods:
The surface potential energy of the isotones 190Hg, 188Pt and 186Os was studied using the Interacting Boson Model Potential program (IBMP), which gives an idea of the deformation that occurs in the nucleus from the deflection of the contour lines and their aggregation in a specific region.
Results:
By applying the Hamiltonian for our isotones in this research, the energy levels were be investigated for ground band, beta band and gamma band, comparing with available experimental data then from the results, draw the potential energy surface and study the deformations that occur in the nuclei of these isotones.
Conclusions :
Determining the limit of these isotones, which have the properties of the limit. These isotones contain some deformation specially 190Hg and 186Os, but there isn’t in 188Pt. This model is good for studying the isotones properties with high even-even atomic number.

Background: The study highlighted the significance of service quality at the University of Babylon and its impact on customer satisfaction. It focused on various elements and indicators related to community service, including the general impression of the university, services provided to citizens, employee cooperation, and transparency.
Mythology :To measure citizen satisfaction with the university, a questionnaire approved by the Ministry of Higher Education and Scientific Research and prepared by the Iraqi Council Secretariat was utilised. The questionnaires were distributed to citizens visiting the University for their Transactions, encompassing four elements and sixteen indicators. The collected data underwent statistical analysis to assess the level of service provided to customers.
Results : The study's findings revealed that the average level of customer satisfaction with the community services offered by the University of Babylon was strongly agreed upon by 40.21% of respondents and agreed upon by 46.47%. A neutral evaluation level was reported by 11.49% of participants, while disagreement was expressed by 1.33% and strong disagreement by 0.50%. These results were determined using the Likert pentameter.
Conclusions: Overall, the study demonstrated that the university's community service effectively satisfied customers through the services provided during their visits, phone interactions, or communication via the official university email. This encompassed completing transactions and addressing questions and inquiries.

Background: The impulsive hematopoiesis model is an extension of the traditional hematopoiesis model that incorporates the concept of rapid bursts or "impulses" of blood cell production in response to certain stimuli or conditions. Finding suitable conditions for the oscillation and global attractiveness of a positive periodic solution in impulsive Hematopoiesis model is an a priori goal for periodic versions. Despite some recent additions, there is still a dearth of literature on this topic.
Materials and Methods: By employing the continuation theorem of coincidence degree since the continuous implies the survival of a mature cells for a long time. And by using the same technique of the proof that was used in model without impulsive is establish some new asymptotic properties for oscillation and sufficient conditions for the global attractivity of the solutions of periodic impulsive hematopoiesis model with submitted a new suitable impulsive condition.
Results: In this work asymptotic Properties for oscillating solutions in a periodic impulsive hematopoiesis model is discuss. New sufficient conditions for oscillation of every positive solution around equilibrium and global attractivity of all non-oscillating solutions around the equilibrium is given.
Conclusion: Some published results in the model without impulsive are improved and extended to the periodic impulsive hematopoiesis model. A numerical example is set up to show the accuracy and efficacy of the results that are provided.

Breast cancer is an old disease, but it has significantly spread in the past few periods, which led to the intervention of computer vision to solve the problem of classification and increase the accuracy of diagnosis to help doctors and radiologists. The computer task was not easy at first, but with artificial intelligence, the concept changed. There are several studies in this regard, from which we chose 27 modern studies from the year 2019 to the year 2023 in various ways to come out with results that are the focus of a new start in the classification. This review collected different machine learning methods, deep learning methods, and CNN structures. Through this study, deep learning shows its superiority over other techniques. The convolutional neural network is considered one of the most important techniques that is characterized by high accuracy in classifying medical images.
This study comprehensively reviews various machine learning and deep learning techniques for breast cancer detection. It also shows that deep learning (CNN) technology is the best in giving accurate classification results. The choice of learning algorithm should have high accuracy if applied to medical images because the result is relevant to the patient's life which should be taken into consideration in the design phase.

Background:
The present research includes a study length effect of quadrupole magnet on the properties of charged particles beam passing through it, the work included theoretical analysis using matrix expounding because it is optimum way to be the representative of beam along any optical system.
Materials and Methods:
we used a Matlab program to study the effect of effective length (Lmm) on the basic parameters of quadruple magnet lens. The values of effective length are from (500 mm to 1000 mm) , to determine focal length and the lens power. The results indicated that increasing the effective length led to a decrease in the horizontal and vertical focal length of the system, but for the power lens, the opposite behavior would be occurred.
Results:
The effective length (L) and the focusing factor (k), whose product gives us the reversed focal length of the magnetic lens, are the main parameters that govern the behavior of a charged particle beam passing a set of quadruple magnets. Any alteration in the value of any one of them so provides a new perspective.
Conclusion:
Two measures that are used to characterize lenses are the focal lengths and the lens power. Shorter focal lengths are associated with stronger lenses. The reciprocal of focal length is lens power. It characterizes different optical systems in terms of particle movement and the smallest possible focusing point.

Background: Obesity currently stands as one of the prevailing and widespread endocrine disorders globally, it has evolved into a worldwide epidemic over the last five decades. Adipose tissue, identified as an endocrine organ within the body, plays a role in certain obesity-related conditions including insulin resistance, diabetes mellitus, and atherosclerosis. Adipose cytokines are among the factors derived from adipose tissue and act as hormones. Vaspin, among these adipocytokines, is generated by both visceral and subcutaneous adipose tissues, it serves to regulate the metabolism of adipose tissue and stimulates processes such as the maturation and differentiation of adipocytes.
Materials& Methods: The individuals who participated in this study were 90 women between (18-50) years old. The research encompassed 45 healthy women with regular menstrual cycles, serving as an age-matched control group. In contrast, the second group comprised 45 obese women who had previously been diagnosed with a vitamin D deficiency.
Results: The results showed that there was a significant increase at (P≤ 0.01) in the level of Vaspin, Parathyroid hormone (PTH) and Osteopontin (OPN) in the group2 compared to the control group, while there was a significant decrease at (P≤ 0.01) in Vitamin D3 (VD3), Vitamim K2 (VK2), Phosphorus(P) and Calcium(Ca+2) in group2 compared to the control group.
Conclusion: This study found that vaspin, osteopontin, and PTH show an inverse association with vitamin D3. While vitamin K2, calcium, and phosphorus show a positive association with vitamin D3.

Background: The increasing reliance on Internet-based applications has led to a rise in the number of hackers, posing a significant threat to the security and confidentiality of digital resources. The performance of the Deep Learning (DL) model is greatly impacted by the design of DL architectures, which typically need expert knowledge. The intrusion detection results can be enhanced by the model by adjusting certain hyper-parameters. The right selection for the best hyper-parameters of the model helps to improve the detection performance.
Materials and Methods: This paper studied the effect of some hyper-parameters used in the classification algorithm for improving the performance of intrusion detection models. Restricted Boltzmann Machine (RBM) and Multilayer Perceptron (MLP) are used to identify the best values in terms of the number of hidden nodes, the number of epochs, and the size of batches used to train the UNSW-NB15 dataset to enhance the accuracy and reduce the implementation time for detecting the attack.
Results: Different numbers of hidden neurons, epochs, and batch size were used to prove which hyper-parameter had the most effect on the performance in terms of accuracy and implementation time to detect attacks.
Conclusion: Building a model and refining it with appropriate hyper-parameter values leads to better design of the model with high performance. The hyper-parameters must be chosen in a way that enhances the performance of the model in terms of increasing accuracy and reducing the implementation time.

Information Extraction refers to the systematic technique of obtaining valuable information from ‎unstructured ‎texts. Named Entity Recognition is a part of information extraction, and is the ‎process of extracting named entities of interest from text, such as person names, places, events, ‎and entities, among others. Named Entity models are useful in critical situations where time and ‎accuracy are important, such as when crime analysts need particular information about a crime case ‎to help them solve it. In the crime domain, police and crime analysts need immediate information on certain crime cases to solve the crime or prevent it from happening again. Crime news documents consist of details on crimes and these details make these documents beneficial. crime analysts are able to quickly and accurately extract beneficial ‎information from unstructured text. With the increase in crime rates all over the world because of ‎the increase in the population, many Named Entity models have been proposed to help crime ‎analysts solve crime cases. Many studies have been conducted on the performance of these methods based on general News wire articles. This work reviews several Named Entity models used for the crime ‎domain.

Background:
The purpose of this study is to demonstrate the effects of thyroid hormone testing and other variable biochemical on childhood growth hormone insufficiency.

Materials and Methods:
There are thirty (30) kids in the growth hormone deficiency group and thirty (30) kids in the control group, ages five to twelve. The demographic data of every participant is documented. Blood samples are obtained for the following types of laboratory analysis: Serum total T3, total T4, and TSH growth hormone levels were measured using kits. While the quantification of fasting blood sugar (FBS),total cholesterol( TC),triglycerides(TG), high density lipoprotein HDL, low density lipoprotein LDL, and very low density lipoprotein VLDL was done automatically.

Results:
While there no statistically significant was difference in FBS, TC, HDL, or LDL between the children with GHD and the control group across the several sets of biochemical data, there is a very noticeable reduction in TT4 and TSH in GH deficient children when compared to the control group. There was no statistically significant difference between the two groups about to TT3 .

Conclusion:
The findings lead us to the conclusion that a key contributing factor to children's lack of growth hormone is thyroid hormone imbalance, and that early diagnosis of both the thyroid gland and growth hormone levels in children is crucial to preventing short stature in them.

Background:
The active levels of natural radioactivity Potassium-40, Uranium-238, and Thorium-232 were examined and evaluated in various soil samples from Al-Hilla city by analyzing the results of these samples and comparing them to internationally accepted levels.
Materials and Methods:
30 soil samples were collected from different areas in the city of Hilla at a depth of 10–15 cm and examined using a gamma-ray spectrometer.
Results:
The radioactivity rate for U-238 was (9.36±0.144) Bqkg-1, while it was (16±0.148) Bqkg-1 for Th-232 and (141.5±0.894) Bqkg-1 for K-40. The study's findings showed that the average radiation effects, such as Radium equivalent (Raeq), the outdoor external dose (Dout), the indoor external dose (Din), the external hazard index (Hex), the internal hazard index (Hin), the representative level index (Iγ), the annual effective dose equivalent (AEDE), and the lifetime cancer risks (ELCR), are as follows: (43.13) Bqkg-1, (20.16) nGyh-1, (37.67) nGy/h, (0.12), (0.11), (0.32), (0.185) mSvy-1, and (0.69) x10-3, respectively.
Conclusions:
The examination of the echelons of naturally occurring radioactivity in the areas in the center of Hilla has produced a wealth of data demonstrating that the measured concentrations of natural radionuclides are within acceptable bounds and represent typical levels of radioactivity.

Background:
In this paper, we conducted a comparison of a number of deep learning networks in detecting Covid-19 disease based on X-ray and CT-scan images.
Materials and Methods:
An eight different deep learning network types (ResNet50, Mobilenetv2, Densnet201, SqueezeNet, Efficientb0, Googlenet, VGG19, and Alexnet25) are investigated to detect the COVI9-19 based on the X-ray and CT-scan images. A transfer-learning technique is adopted in the training phase for all networks with different datasets. The networks are trained and tested on 70% and 30% of the dataset, respectively.
Results:
The confusion matrix is calculated in the testing phase and the evaluation metrics including F1 score, accuracy, precision, specificity and sensitivity are calculated from the confusion matrix. The comparison results demonstrate that the classification accuracy when using X-ray dataset is better than that of using CT-scan datasets. Moreover, the Mobilenetv2 delivered the greatest results for different datasets in which the accuracy is greater than 99% for X-ray images and the accuracy is less than 80% for CT-scan images .
Conclusion:
Our conclusion is that the using of Mobilenetv2 network with the X-ray images is more suitable than the others.

Background:
Several studies have confirmed the importance of using the body condition assessment process in dairy cow breeding stations, as it is one of the means that helps in the success and efficiency of the management used, improving feeding programs and monitoring the health status of the cows, thus increasing pregnancy and production rates in the herd.
Materials and Methods:
The study conducted at the Diwaniyah cows station included Holstein cows in parity 2, were classified according to body condition at calving into a 2.5–3 point (BCS1) Included 17 cows, a 3-4 point (BCS2) Included 20 cows, and a 4-5 point (BCS3) Included 13 cows Depending on the 1-5 grade scale for dairy cows. Production was recorded weekly during the study, The percentages of its components were determined at peak production and three months after calving.
Results:
BCS2 group was significantly superior (P≤0.01) in average daily and total production compared to the other groups. BCS2 and BCS3 groups were significantly superior (P≤0.01) in the average daily production at the peak compared to BCS1 group. BCS3 group was significantly superior (P≤0.05) in lactose concentration at peak production, and in the concentration of lactose and protein after three months of production compared to BCS1 group.
Conclusions:
Body condition at calving affects the productive performance of cow. Body condition assessment determines the energy reserve in the body during the production cycle to prepare the appropriate nutritional program, meet production requirements, maintain the health of cows, and protect them from metabolic diseases.

Background
Legumes, scientifically classified as Fabaceae or Leguminosae, constitute the third most extensive family of flowering plants, surpassed only by (Orchidaceae) and asters (Asteraceae). The genus Vicia faba L., which is temperate and herbaceous in nature, belongs to the legume tribe Vicieae of the Papilionoideae. Legumes and cereals are the two most important flowering plants used in agriculture. Legumes are useful as human and animal food, and as soil-improving components of agricultural and agroforestry systems.
Materials and methods
The present study involved the extraction of DNA from the foliage of the Vicia faba L plant, followed by its amplification using three primers for the purpose of conducting ISSR analysis by polymerase chain reaction (PCR).
Results
This process resulted in the generation of a total of 30 DNA fragments, which were then able to be assessed across all genotypes. The aggregate count of polymorphic markers and the mean percentage of polymorphism were recorded as 43.33%.
Conclusion
The findings of our study indicate a substantial degree of genetic diversity within the fenugreek treatments. This discovery also suggests that the ISSR technique provides more comprehensive information for assessing genetic diversity and connections among populations of Vicia faba L.

Background:
The risks of natural radioactivity emanating from the radionuclide’s Potassium-40, Uranium-238, and Thorium-232 are measured in various soil samples from Al-Hilla city, and the extent of their cumulative impact on human health is determined.
Materials and Methods:
Natural radioactivity was measured in 30 soil samples collected from different areas at a depth of 10–15 cm and examined using NaI (TI).
Results:
The radioactivity rate for U-238 was (9.36±0.144) Bqkg-1, while it was (16±0.148) Bqkg-1 for Th-232 and (141.5±0.894) Bqkg-1 for K-40. In this research, radiation risks are evaluated by measuring risk parameters. The average radium equivalent was (43.13) Bqkg-1; the average outdoor external dose and the average indoor external dose in nGyh-1 were (20.16) and (37.67). The average values of the external hazard index, the internal hazard index, and the average representative level index (Iγ) were (0.12), (0.11), and (0.32), respectively, and the average annual effective dose equivalent is (0.185) mSvy-1, and the average lifetime risk of cancer is (0.69) x 10-3.
Conclusions:
After looking at the natural radioactivity of radionuclides in soil samples taken from the Hillah regions, we found that the amounts of radionuclides were within acceptable ranges and standard radioactivity.

Background
In this paper, we propose two new techniques called the Sawi transformations and Sequential approximations method, which are applied to solve multi-higher order linear fractional differential equations with constant coefficients. In which Riemann-Liouville and Caputo define the fractional derivatives and fractional integral, fractional formula for all types have been derived, we first developed the Sawi transform of foundational mathematical functions for this purpose and then described the important characteristics of the Sawi transform, which may be applied to solve ordinary differential equations and fractional differential equations. Following that, the authors found an exact solution to a particular example of fractional differential equations.
Materials and Methods
With these methods good exact and approximate solutions can be obtained with only a few iterations for the Sequential approximations method, and the approximate solutions guarantee the desired accuracy. For more validation of the methods, and fractional formula of sawi transformation method work such as other transformation.
Results: The exact and approximation solutions for some fractional differential equations are obtained, and several examples are explained to demonstrate the efficiency and implementation of the proposed methods.
Conclusions
It is clear from reading the literature on fractional differential equations (FDEs) that the Sawi transformation method is a workable solution to these problems. To use this approach, which also completely resolved fractional differential equations, the FDEs must be simplified.

A person is said to be stigmatized when they are subjected to discredit, devaluation, and shame as a result of the characteristics or attributes that they exhibit. In most cases, the effects of stigma on a person's social life are unpleasant and include feelings of alienation, rejection, marginalization, and discrimination. Stigma can affect a person's illness and treatment, including their ability to get professional and suitable medical care for their condition, if it is connected to a health condition like mental illness. It has been pointed out that mental health professionals are not the only ones impacted by stigma; patients' loved ones feel it, too. The cultural and contextual value systems of a society, which can shift over time and between different settings, have a significant impact on stigma. On the other hand, there is a paucity of data regarding the nature of the stigma that patients suffering from mental illness and nurses working in mental health care face in Iraq. These days, stigma's aftereffects are so pervasive that they pose a threat to public health in nearly every Western nation. The fallout might range from social isolation to prejudice towards those with mental illness in the job or classroom. This leads to poor self-esteem and confidence, which in turn hinders social and occupational functioning and therapy for people with mental illness.