RESTful web services for an ERP system for social services

Abstract. The advances in hardware and software have been rapidly integrated by organizations, especially in the healthcare sector, demanding new approaches for software to provide more reliable products, under well-known quality standards. This thesis investigates, designs and implements a set of operationally crucial RESTful web services for Invian Oy ERP system, DomaCare. Today, DomaCare is one of the fastest growing and developing software solutions in Finland in the healthcare sector. Thousands of satisfied healthcare professionals across Finland use DomaCare daily. DomaCare is a versatile ERP system designed specifically for the social sectors. This thesis describes the theoretical part of software architecture and software architectural style, which support understanding REST. Second, the thesis introduces the environment and tools required for the development stage. Third, the thesis presents the action and sequence diagrams for each use case to support the overall understanding of the system in a higher level of abstraction. Moreover, unit tests were implemented in this thesis for each use case, and, finally, the approach which was employed to validate the system is presented. In conclusion, the thesis concludes that based on the literature review, implementation, the results obtained from the unit tests, and the system validation fulfilled the goals set for this thesis.Tiivistelmä. Laitteistojen ja ohjelmistojen tekniikkaa on nopeasti integroitu organisaatioihin erityisesti terveydenhoitoalalla. Tämä vaatii ohjelmistojen osalta uudenlaisia lähestymistapoja, jotta jatkossa voidaan tarjota luotettavampia ja tunnettujen laatustandardien mukaisia tuotteita. Tässä diplomityössä esittelen tutkimusvaihetta, suunnitteluprosessia sekä toteutustapoja toiminnallisesti tärkeän, REST-arkkitehtuurimallia noudattavan webrajapinnan toteuttamiseksi Invian Oy:n DomaCare-toiminnanohjausjärjestelmässä. Tänä päivänä DomaCare on yksi Suomen terveydenhuoltoalan nopeimmin kasvavista ja kehittyvistä ohjelmistoratkaisuista. Sitä käyttävätkin tuhannet tyytyväiset terveydenhuollon ammattilaiset päivittäin ympäri Suomen. DomaCare on monipuolinen asiakas- ja toiminnanohjausjärjestelmä, joka on suunniteltu erityisesti sosiaalialoille. Diplomityössäni kuvaan verkkopohjaisten järjestelmien arkkitehtuurisuunnittelun sekä REST-arkkitehtuurimallin teoreettista puolta. Lisäksi tuon opinnäytetyössäni esille kehitystyöhön tarvittavan ympäristön ja työkalut sekä toiminta- ja sekvenssikaaviot kullekin käyttötapaukselle, jotta se tukisi yleistä järjestelmän ymmärtämistä korkeammalla abstraktiotasolla. Lisäksi esittelen tutkimuksessani kaikki toteutetut yksikkötestit kussakin käyttötapauksessa sekä lopuksi myös ne lähestymistavat, joita käytettiin systeemin vahvistamiseksi. Päädyn johtopäätökseen, että diplomityössäni esitellyt kirjallisuuskatsaus, toteutus ja yksiköiden testeistä saadut tulokset täyttivät tämän tutkimuksen tavoitteet

Isolation of Lactobacillus salivarius from Children and Purification of Bacteriocin to Inhibition Cancer Cell in Vitro

Bacteria being used to make anticancer agents could provide an extra source of lead compounds for the pharmaceutical industry.  Bacterium Lactobacillus salivarius produce compounds that selectively inhibit growth of human cancer cells Lactobacillus salivarius naturally produces a compound called Bacteriocins.  Bacteriocins are bacterial proteins produced to prevent the growth of competing microorganisms in a particular biological niche and we can use it as antineoplastic. The aim of this study was to isolate bacteriocin produced by lactic acid bacteria. A preparation of bacteriocin from a strain Lactobacillus salivarius has long been shown to have antineoplastic activity against a variety of human tumor and animal tumor cell lines in vitro. A total of 60 LAB  were isolated from children stool 45 isolate showed a clear antimicrobial activity against indicator strain Streptococcus aureus and by used sodium phosphate buffer (pH8) from an 80% ammonium sulfate precipitate. The inhibition  activity was determent by well diffusion assay method technique, Bacteriocin purification processes were carried out by using ion-exchange (Trisacryl SP) and gel filtration chromatography (Sephacryl – S300). The apparent molecular mass of partially purified bacteriocin was 15. 848 kDa,  Cell Culture was maintained in RPMI 1640 medium supplemented with 10% (vol/vol) fetal calf serum,  Cytotoxicity of bacteriocin was assessed on human cell line (RD) and animal cell line (MDCK) cell viability after incubation for 48 h in medium containing 500AU/ml (1.15 mg/ml). Both cell types used in this study were sensitive to bacteriocin and the bacteriocin appeared to inhibit proliferation of tumor cell line. The animal cell line was more sensitivity than human cell line

Assessment of Natural Radionuclides in Powdered Milk Consumed in Iraq

The activity concentrations of 226Ra232Th, and 40K radionuclides were measured for 10 brands of powdered milk samples consumed in Iraq,which are imported from different countries.The main detected activity corresponding to 40K with average activity of 290.661 BqKg-1, while the average activities of 226Ra and232Th were below the detection level (B.D.L.).Results are compared with those of different countries worldwide.The total average annual effective doses due to intake of 40Kfrom the ingestion of the powdered milk for children (2-7, 7-12, 12-17)y and adults (≥ 17y) were estimated to be82.21, 50.90, 29.75 and 22.55 µSvy-1, respectively. These results indicate no significant radiation dose to the public. The resulting data may serve as base-line levels of activity concentration in powdered milk in the area of study. Keywords: Natural Radioactivity, Milk, Ingestion dose, Hazard quotient

Inhibición de genes de enterotoxinas de Staphylococcus aureususando extracto de plantas

Introduction: Enterotoxigenic Staphylococcus aureus is an important pathogen that causes septicemia and bacteremia and is often associated with serious complications, such as endocarditis and osteomyelitis. Some Staphylococcus enterotoxins require only minute quantities to be toxic in humans. The present study focused on investigation how to remove this problematic issue. Objectives: This study was conducted to inhibit S. aureus enterotoxin genes that obtained from positive blood culture bottles of patients at the pediatric hospital in Sulaimania city. Methods: Twenty five isolates of S. aureus were isolated among 100 positive blood culture bottles and determined the strains that produce enterotoxins through culture method. Then, the enterotoxin genes that located on plasmids were cured by two medicinal plants (Eugenia caryophyllata and Cinnamomum zeylanicum). Results: The results showed that nine out of 25 isolates were released enterotoxins from which the plasmid encoding enterotoxin genes were confirmed in four of them. And, two of the isolates were transferred to recipient DH10B E. coli isolate successfully. Methanol extracts of (E. caryophyllata and C. zeylanicum) were used at sub minimum inhibition concentration as curing agents. Conclusion: Methanol extracts of (E. caryophyllata and C. zeylanicum) have grate effect on eliminating the plasmidsencoding enterotoxin gene of S. aureus

Development of Anti-bodies against Infliximab in Iraqi Patients with Rheumatoid Arthritis.

Background: Rheumatoid arthritis is a common chronic and destructive autoimmune arthropathy .Treatment with infliximab gives great improvement to a large numbers of patients with RA ,however, in some patients after prolonged treatment infliximab can induce anti-infliximab antibodies formation and result to loss of infliximab efficacy and active persistent disease. Objective: to investigate the frequency of anti-infliximab antibodies in Iraqi patients with rheumatoid arthritis. Patients and methods: fifty Iraqi RA patients(36 females and 14 males) compared with 50 control( 25 healthy control and 25 case control (patients with RA on other treatment) ) were included in this study from begging of March 2014 till end of September 2014.All patients were diagnosed by full history, complete clinical examination and laboratory test. Anti-infliximab antibodies were meatured using enzymelinked immunosorbent assay in serum of Iraqi patients with RA treated with infliximab more than 3 months duration. Results: Antibodies to infliximab were detected in 35(70%) Iraqi RA patients , while the patients without detectable antibodies against infliximab were 15(30%),also there were no anti-infliximab antibodies in the control groups. Conclusion: In this study, nearly three quarter of the Iraqi RA patients treated with infliximab developed anti-infliximab antibodies

Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D CNNs have shown improved accuracy in the classification of ASD compared to traditional machine learning algorithms, on all these datasets with higher accuracy of 99.45%, 98.66%, and 90% for Autistic Spectrum Disorder Screening in Data for Adults, Children, and Adolescents respectively as they are better suited for the analysis of time series data commonly used in the diagnosis of this disorde

COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT

تستخدم الإشارات الصوتية التي يولدها جسم الإنسان بشكل روتيني من قبل التخصصين في البحوث والتطبيقات الصحية  للمساعدة في تشخيص بعض  الامراض أو تقييم تقدم المرض. وبالنظر إلى التقنيات الجديدة ، من الممكن في الوقت الحاضر جمع الأصوات التي يولدها الإنسان ، مثل السعال. ويمكن بعد ذلك اعتماد تقنيات التعلم الآلي المستندة إلى الصوت من أجل التحليل التلقائي للبيانات التي تم جمعها مما يوفر معلومات قيمة غنية من إشارة السعال واستخراج الميزات الفعالة من فترة زمنية محدودة الطول تتغير كدالة للوقت. في هذا البحث يتم اقتراح وتقديم خوارزمية  للكشف عن COVID-19 وتشخيصه من خلال معالجة السعال الذي يتم جمعه من المرضى الذين يعانون من الأعراض الأكثر شيوعًا لهذا الوباء. تعتمد الطريقة المقترحة على اعتماد مزيج من تحليل القيمة المفردة (SVD) وتحويل المويجات المنفصل (DWT).  وقد أدى الجمع بين هاتين التقنيتين لمعالجة الإشارات إلى اتباع نهج جيد للتعرف على السعال ، حيث يولد ويستخدم الحد الأدنى من الميزات الفعالة. وفي هذه الخوارزمية المقترحة يتم تطبيق الترددات المتوسطة (mean and median)، والمعروفة بأنها أكثر الميزات المفيدة في مجال التردد ، لإنشاء مقياس إحصائي فعال لمقارنة النتائج. بالإضافة إلى الحصول على معدل كشف وتمييز عاليين ، تتميز الخوارزمية المقترحة بكفاءتها حيث يتم تحقيق تخفيض 200 مرة، من حيث عدد العمليات. على الرغم من حقيقة أن أعراض الأشخاص المصابين وغير المصابين في الدراسة بها الكثير من أوجه التشابه ، فإن نتائج التشخيص التي تم الحصول عليها من تطبيق نهجنا تُظهر معدل تشخيص مرتفعًا، والذي تم إثباته من خلال مطابقتها مع اختبارات PCR ذات الصلة. نعتقد أنه يمكن تحقيق أداء أفضل من خلال توسيع مجموعة البيانات ، مع تضمين الأشخاص الأصحاء.Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopting a combination of Singular Value Decomposition (SVD), and Discrete Wavelet Transform (DWT). The combination of these two signal processing techniques is gaining lots of interest in the field of speaker and speech recognition. As a cough recognition approach, we found it well-performing, as it generates and utilizes an efficient minimum number of features. Mean and median frequencies, which are known to be the most useful features in the frequency domain, are applied to generate an effective statistical measure to compare the results. The hybrid structure of DWT and SVD, adopted in this approach adds to its efficiency, where a 200 times reduction, in terms of the number of operations, is achieved. Despite the fact that symptoms of the infected and non-infected people used in the study are having lots of similarities, diagnosis results obtained from the application of the proposed approach show high diagnosis rate, which is proved through the matching with relevant PCR tests.  The proposed approach is open for more improvements with its performance further assured by enlarging the dataset, while including healthy people

Exploring the quality of life of cosmetic users: A cross-sectional analysis from eight Arab countries in the Middle East

Background The use of cosmetic products is growing in dominance in the Arab population, making it essential to measure its effects on users. The production of cosmetics has been largely driven by consumerism and a bid to keep abreast with the latest trends in the beauty industry with less attention on how the users' quality of life (QoL) is affected. Aims This study aims to investigate the effect of cosmetic products on users' quality of life in eight Arab countries. Methods A cross-sectional study was carried out using an online data collection approach. A validated and specialist instrument tool called BeautyQoL, which consists of five domains and a total of 52 questions, was distributed to a sample of 2219 cosmetic users. Descriptive and inferential statistical analysis was done using SPSS® version 26.0. Results The mean age of participants was 34 ± 11.25 years, and more women were represented in the sample (71%) than men. The majority of respondents had oily skin type (39.6%) and tan skin tone (30.4%). QoL through cosmetic use is computed with a mean score of 51 out of 100. The users' mean score satisfaction from cosmetic use is centred on attractiveness (56.1), followed by self-confidence (51.8). Cosmetics have a statistically significant effect on participants who are young adults, women, single, and employed with high income. As the respondents' skin tone deepens from very fair to dark, the mean score for each domain significantly increases, whereas when skin type changes from very oily to dry, the mean score for each domain decreases. Conclusion The effect of cosmetics on the users' QoL is limited, contrary to the narrative commonly portrayed in cosmetics' advertisements. Therefore, the use of cosmetics among the Arab population should be from an informed perspective of their specific needs instead of conforming to the viral trends pedaled by influencers and bloggers on social media, which might be irrelevant for them.Open access publishing facilitated by Monash University, as part of the Wiley - Monash University agreement via the Council of Australian University Librarians. [Correction added on 5 July 2022, after first online publication: CAUL funding statement has been added.]Scopu

SPARC 2017 retrospect & prospects : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2017 SPARC conference. This year we not only celebrate the work of our PGRs but also the 50th anniversary of Salford as a University, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 130 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to exploit this great opportunity to engage with researchers working in different subject areas to your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers