Background: Oral health plays an important role in maintaining life functions and quality of life. Periodontal disease can vary with respect to bacterial etiology, host response, and clinical disease progression. A key role of genetic effects has suggested distribution of lesions and severity of destruction in each individual. Many diseases, particularly digestive disorders, cancer, and infection, show preferences among the ABO blood types. Knowledge of blood groups and their association with oral diseases is very important, as it may help in early diagnosis and treatment strategies‏. Objectives: The study aimed to investigate the distribution of patients with oral and dental health problems according to age, regions, Socio-demographic Variables, and blood groups in the Tripoli region. Material and Methods: The present study was conducted on 200 patients with oral and dental health problems attending six medical centers in Tripoli region from the 01^st March 2022 to the 01^st June 2022. Also, 100 healthy individuals without any oral and dental health problems or any other diseases were recruited as a control group. This study was approved by the Research and Ethical Committee of the medical centers and Libyan Academy of graduate studies. One ml of venous blood was withdrawn from each participant in the study for determination of blood groups. The data were compared using Chi-Square using SPSS Statistics for Windows, Version 25. Results: The results showed that the mean age of the patients was 43.03±13.82 years. The higher distribution of patients was 58 patients (29%) in the age group (26-35) years while the lower distribution was 10 patients (5%) in the age group (66-75) years. The distribution of patients according to the region were 81.5%, 13%, 4%, and 1.5% in Tripoli, South Tripoli, West Tripoli, and East Tripoli, respectively. The Distribution of patients according to occupation were 4.5% Students, 30% Housewives, 10.5% Employers, 12.5% Teachers, 14% Nurses, 7.5% Doctors, 12.5% Laboratory Technicians and 8.5% Freelance workers. The distribution of patients according to levels of education were 23.5% Pre-Secondary, 19% Secondary, 46% Bachelor's or equivalent, and 11.5% Master's or equivalent. The distribution of patients according to marital status were 26% single and 74% married. The distribution of patients according to oral and dental problems were 5% with bridge, 8% with missing teeth, 86% with dental caries, 63.5% with bleeding of gum, and 25.5% with swelling of gum. The degrees of gingival erythema among patients were 36.5% mild, 38% moderate, and 25.5% severe. The degrees of gingival inflammation among patients were 36% mild, 38.5% moderate, and 25.5% severe. The distribution of A, B, AB, and O blood groups showed a significant (P=0.000) difference between healthy individuals and oral and dental health problems among patients that, were 54%, 12%, 4%& 30%, and 21.5%, 9%, 3.5% & 66%, respectively. Also, the distribution of A⁺, A^-, B⁺, B^-, AB⁺, O⁺, and O^- blood groups showed a significant (P=0.000) difference between healthy individuals and patients with oral and dental health problems that, were 49%, 5%, 10%, 2%, 4%, 25%, & 5%, and 18%, 3.5%, 8%, 1%, 3.5%, 60%& 6%, respectively. But, the distribution of Rh⁺ and Rh^- blood groups showed a non-significant (P=0.695) difference between healthy individuals and patients that, were 88% & 12%, and 89.5%& 10.5%, respectively. Conclusion: It can be concluded that the mean age of the patients with oral and dental health problems was 43.03 years and the higher distribution of patients was in the age group (26-35) years. The higher distribution of ABO blood groups was O blood group among patients especially O⁺ blood groups. The distribution of Rh+ and Rh- blood groups were showed a non-significant difference between healthy individuals and patients with oral and dental health problems. Further studies are needed to confirm these results.

Many attempts have been made to repurpose existing and approved drugs for the treatment of COVID-19 infection. This involves anti-malarial drugs such as hydroxychloroquine and chloroquine, which have been shown to be less successful than initially believed, with a substantial risk of often fatal complications and interactions. This also involves Remdesivir, which has been shown to decrease recovery time significantly in hospitalized patients. However, for patients who are not yet hospitalized, there is no currently accepted treatment. Treating patients before they need to be admitted or even prophylactically could greatly decrease the load on hospitals, protect healthcare workers and reduce the spread of COVID-19. An in-vitro study indicated that Ivermectin was dynamic against COVID-19-infected cell. Ivermectin has antimicrobial, antiviral, and anticancer, immunomodulatory properties. This drug could reduce the viral load in COVID-9 infected patients, with potential effect on disease progression and spread. Therefore, Ivermectin may be a therapeutic choice for treatment of COVID-19, however, there is still a lack of evidence-based studies to support ivermectin treatment of patients with COVID-19.

The rapid spread of COVID 19 outbreak has put a heavy burden on human society and is a great challenge for health care workers. The present study aims to assess the perceptions of nursing personnel regarding challenges in usage of PPE during COVID 19 pandemic and to find out the association between severity of physical symptoms and selected personal variables of nursing personnel. A quantitative approach with descriptive survey research design was used for the study. Web based self-administered questionnaire, rating scale and checklist were developed and distributed among study participants in the “Google forms”. A total of 134 participants were included in the study. Out of the 134 participants, 85(63.4%) nursing personnel were working in the government sector and 49(36.6%) of nursing personnel were working in the private sector. The top five challenges in the usage of PPE ranked based on self-reported data were; 1. difficulty to meet the basic needs such as food and fluids, 2. difficulty to meet elimination needs, 3. Unable to relax, 4. difficulty to meet hygienic needs and 5. disconnected with friends and family during working hours. Analysis of physical symptoms experienced by the nursing personnel showed that 41(30.6%) had mild symptoms, 54(40.3%) had moderate symptoms and 39(29.1%) had severe symptoms experienced owing to PPE usage. The most common physical symptoms reported by nurses were heat stress 124(92.5%), head ache 120(89.6%), exhaustion 117(87.3%) and dryness in throat (86.6%). There were no significant association between physical symptoms of nursing personnel and selected personal variables at 0.05 level of significance.

It is known that seasonal influenza virus vaccination is important to be taken every year among healthcare workers (HCWs) to avoid transmission of influenza virus and its complications inside the workplace. The reason behind the importance of vaccination is that HCWs are at high risk to be infected with influenza virus. Among the studies addressing the rates of influenza vaccine status among HCWs, a study was conducted in three Middle East countries where the vaccination rates were 24.7%, 67.2%, and 46.4% in United Arab Emirates, Kuwait, and Oman, respectively. Now, after the pandemic of COVID-19 there are beliefs that vaccination with influenza virus could decrease the deaths from COVID-19. A recent retrospective cohort study to detect the effect of seasonal influenza vaccine on the deaths among COVID-19 patients showed that the individuals who didn’t take the influenza vaccine in the last year before being infected with COVID-19 had a higher risk of being hospitalized when compared with patients who took the vaccine. In conclusion, seasonal influenza vaccine could have an important role in the prevention of COVID-19. Seasonal influenza vaccine coverage should be improved among HCWs. New tailored health education programs to improve the attitudes and beliefs of HCWs towards seasonal influenza vaccine during the era of COVID-19 are strongly and urgently needed.

The present study raises the problem of empathy of caregivers vis-à-vis patients in a covid/post-covid context. It is based on the observation that health workers are increasingly invaded by excessive fear and persistence of COVID-19 contamination. This induces avoidance, a certain suspicion, persecution and indifference/coldness towards patients, and plunges them into a strong insidious emotional deficiency. These attitudes, which are significantly close to paranoid and phobic access, seem to gradually dominate therapeutic interactions within hospitals. Freudian and Rogerian psychoanalysis advocates empathetic/benevolent listening, positive consideration and unconditional acceptance of the patient as ethical and deontological indispensable principles for any therapeutic evolution. Thus, it is predicted that within hospitals, the current non empathetic attitudes of care towards patients have their origin in a generalized covid-phobic atmosphere that develops a quasi-dominant paranoia in caregivers. Using a subscale of caregiver's Covid-phobic quasi-paranoia, and the one of caregiver's empathy in a covid/post-covid context, the data were collected from 126 participants including 55 nursing assistants, 61 state-certified nurses and 10 doctors, chosen at random from the staff of three (03) health facilities in the city of Bafoussam, MIFI department, West Cameroon region, including one (01) public district medical center (CMA) and two (02) private hospitals (clinics). After analysis, the results obtained sufficiently demonstrate that within the health institutions of West Cameroon, the higher the professional level of the caregiver, the more the severity of his quasi-paranoid covid-phobic accesses is significant, and the less he expresses an authentic empathy towards the patients who arrive at the hospital. This implies that in this period of health crisis, caregivers must reinvest in a real function of providers of affectivity and relay of empathy at the bedside of the patient both in hospital and outpatient. Thus, a real systematical vaccination operation may insure their total immunity and better reduce their quasi-paranoid empathy in this generalized Covid-phobic context.

High levels of occupational noise and vibration remain a problem in all regions of the world. In Nigeria, 12−15% of the workforce are exposed to these hazards by WHO, 2001. This research intends to achieve the following objectives; To assess the noise emitted during the moulding of various types of blocks, to determine the level of vibration induced to workers of block moulders during activities and to determine the effect of noise and vibration on workers. The following materials and equipment were used; QT40B manual block moulding machine, LM2-45 Mobile Block moulding Machine, Lister powered block moulding machine, QTJ4-40 block moulding machine using 9 and 6 inches Plates, Vibrometer and Noise monitor. The workers were exposed to noise levels above 75dB and vibration levels above 5ms-2 set as upper limit values in the Directive 44/EC from 2002 – on the Minimum Health and safety Requirements Regarding to Exposure of Workers to the Risk Arising from Physical Agents Vibration.

The equipment used in the construction industry is usually associated with a high impact on the environment. Although sustainable design has shown to be a main player among the initiatives focused on reducing environmental impact, it has been driven by the workers and processes, leaving the equipment endeavors in more restrictive and later stages. The equipment industry has been a constant target of environmental standards and economic pressure, but the increasing technological development allows it to respond to sustainability and safety expectations while enhancing its performance. However, there are still several limitations that lead this sector to be one of the last to reach upgrading levels in terms of development. A study identified some gaps in the equipment design that require a greater effort to effectively support the workers and companies towards sustainable construction. This chapter is based on a study aiming to understand the consolidated knowledge of technologically sustainable equipment design and to identify the challenges left for its full development. The findings support the development of innovative eco-friendly equipment, taking into consideration sustainable materials and product guidelines, as well as green economy initiatives. It also supports complex system approaches and safety by design specificities to establish a corporate knowledge of sustainable equipment and align it with the new regulations of the construction industry. The chapter introduces the context of construction equipment in terms of new challenges when faced with the need to provide construction work with a greater capacity for safety, from an environmental and energy efficiency perspective, and within the paradigm of sustainability. Then, it presents the concept of sustainable equipment considering its principles, followed by a characterization of the agents involved in its life cycle.

Self-service business intelligence (BI) platforms have become essential applications for exploring, analyzing, and visualizing business data in various domains. Here, we envisage that the business intelligence platform will perform automatic and autonomous data analytics with minimal to no user interaction. We aim to offer a data-driven, intelligent, and scalable infrastructure that amplifies the advantages of BI systems and discovers hidden and complex insights from very large business datasets, which a business analyst can miss during manual exploratory data analysis. Towards our future vision of autonomous analytics, we propose a collective machine learning model repository with an integration layer for user-defined analytical goals within the BI platform. The proposed architecture can effectively reduce the cognitive load on users for repetitive tasks, democratizing data science expertise across data workers and facilitating a less experienced user community to develop and use advanced machine learning and statistical algorithms.