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ABSTRACT: Soybean meal (SBM) is a commonly used protein source in feed. Yeast microbial protein could be used as a substitute for SBM, but its effect on cheese-making properties and yield is not known. Norwegian Red dairy cows (n = 48) in early or mid lactation were divided in 3 groups and fed a ration consisting of grass silage and concentrate, where the concentrates were barley based but with different additional protein sources. These were: completely barley based with no additional protein source (BAR), additional protein from SBM, or additional protein from yeast (Cyberlindnera jadinii; YEA). The SBM and YEA concentrates had a higher protein content than the barley concentrate. Four batches of cheese were made from pooled milk from each of the 3 groups of dairy cows. Milk samples were collected 5 times during the experiment. Milk from cows fed BAR concentrate showed inferior cheese-making properties (lower casein content, longer renneting time, lower content of phosphorus, and lower cheese yield) compared with SBM and YEA concentrates. Overall, SBM or YEA bulk milk had similar cheese-making properties, but when investigating individual milk samples, YEA milk showed better coagulation properties.

ABSTRACT: Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake.

This study investigates the relationship between the transformational leadership of academic leaders and the job satisfaction of academic staff in polytechnic colleges located in the North Shewa Zone of Ethiopia. This study used a correlational research design and simple random sampling techniques to select 264 academic staff members. Respondents completed a rating version of the multifactor leadership questionnaire and a job satisfaction survey. Data analysis uses descriptive and inferential statistics like Pearson correlation and linear regression. The study found that transformational leadership was found to positively correlate with and predict academic staff job satisfaction, though it was weak. The findings also revealed that academic staff was dissatisfied with their jobs, despite perceiving their leaders as having a moderate degree of attributes of transformational leadership style. Educational planners can use the findings to transform administrative and academic leaders' leadership programs. Leadership training boosts academic staff morale and job satisfaction. Job satisfaction also improves staff retention and minimizes turnover. Thus, academic leaders should grow themselves and seek opportunities to improve their transformational leadership skills. To better understand the leadership style elements that have the greatest impact on job satisfaction, further research is necessary due to the limited variability or unexplained variance in the ability of transformational leadership styles to predict job satisfaction. Further investigation is also needed to explore the mediating factors that impact the link between two variables in an Ethiopian context.

Literacy abilities are crucial for economic progress and community welfare, with higher education recognizing them as vital for problem-solving, critical thinking, continuous learning, and effective functioning for both experienced educators and the new student cohorts. The study examined the interplay between organizational learning and departmental performance, and its implications for changes in Ethiopian Public Research Universities. The researchers used the framework that focuses on seven distinct dimensions of organization learning (OL) namely continuous learning, inquiry and dialogue, collective and collaborative efforts of organizational members, empowerment, embedded system, system connection and strategic leadership and departmental performance (DP) which consists of three dimensions teaching-learning, research and community services. The researchers employed embedded mixed methods design (QUAN + qual) to examine the interplay between organizational learning (OL) and departmental performance (DP). The researchers selected four public research universities using simple random sampling technique. Then, they selected 1,176 respondents (969 instructors and 207 department heads) from target population using simple random sampling technique. The researchers adapted standardized questionnaires and collected quantitative data using questionnaires, and analyzed using descriptive statistics (mean & standard deviation), and inferential statistics (multiple correlations, multiple regressions & structural equation modeling). Qualitative data was collected using semistructured interview from 14 key informants who were selected using the purposive sampling technique based on their rich lived experiences of teaching-learning, research and leadership in higher education institutions. The qualitative data was thematically analyzed. The finding of the study showed that the structural equation model fit to the data. It was also found that the correlations between the different dimensions of organizational learning practices and departmental performance ranged between low and moderate. There were positive significant and moderate correlations between each dimension of organizational learning and departmental performance. The organizational dimensions accounted the largest cumulative variance to departmental performance dimensions; research (R[superscript 2] = 40.70%; [beta] = 0.638, p < 0.001); community service (R[superscript 2] = 33.50%; [beta] = 0.579, p < 0.001) and teaching-learning (R[superscript 2] = 24.60%; [beta] = 0.496, p < 0.001). The study showed that the presence of formal and informal organizational learning cultures in universities enhance departmental performances. Therefore, the Ethiopian public research universities should create effective organizational learning systems to improve departmental performances.

In patients with out-of-hospital cardiac arrest (OHCA) who attain return of spontaneous circulation (ROSC), rearrest while in the prehospital setting represents a significant barrier to survival. To date, there are limited data to guide prehospital emergency medical services (EMS) management immediately following successful resuscitation resulting in ROSC and prior to handoff in the emergency department. Post-ROSC care encompasses a multifaceted approach including hemodynamic optimization, airway management, oxygenation, and ventilation. We sought to develop an evidenced-based, goal-directed bundle of care targeting specified vital parameters in the immediate post-ROSC period, with the goal of decreasing the incidence of rearrest and improving survival outcomes. Here, we describe the rationale and development of this goal-directed bundle of care, which will be adopted by several EMS agencies within California. We convened a group of EMS experts, including EMS Medical Directors, quality improvement officers, data managers, educators, EMS clinicians, emergency medicine clinicians, and resuscitation researchers to develop a goal-directed bundle of care to be applied in the field during the period immediately following ROSC. This care bundle includes guidance for prehospital personnel on recognition of impending rearrest, hemodynamic optimization, ventilatory strategies, airway management, and diagnosis of underlying causes prior to the initiation of transport.

Despite the abundance of research linking leadership behaviours to organisational effectiveness in various sectors, there is a lack of empirical studies that investigate how leadership behaviours influence performance in the context of research universities. The present study examined the effects of leadership behaviours on departmental performance in public research universities in Ethiopia. The study employed a quantitatively driven embedded type of mixed methods design. The participants of the study were 1176 academic staff (969 instructors and 207 department heads). They were selected from four public research universities using a simple random sampling technique. In addition, 14 key informants were selected using a purposive sampling technique based on their teaching-learning, research and leadership lived experiences in higher education institutions and interviewed using semi-structured guiding questions. Quantitative data were collected using questionnaires composed of demographic questions and adapted versions of two scales: Multifactor Leadership Questionnaires and a new tool for measuring global academic performance. The quantitative data were analysed using frequency, percentage, multiple correlations and regression, one sample t-test, exploratory factor analysis and confirmatory factor analysis. Version 23.0 of Analysis of Moment Structures (AMOS) and SPSS-23 were used for data analyses. Qualitative data were analysed thematically using open code version 4.03 software. The analyses showed that transactional leadership dimension and teaching-learning dimension of departmental performance were practised predominantly. Dimensions of leadership behaviour were found to be positively and significantly related to dimensions of departmental performance. The joint contributions of dimensions of leadership behaviour were larger than their separate contributions, thereby supporting the formulated alternative hypotheses. Implications of the findings were discussed.

Plantations of fast-growing tree species are important in climate change mitigation efforts because of their enormous potential for carbon storage and the potential affected mainly by tree species type and composition, which influence particular carbon pools in the system. This study estimates biomass and soil organic carbon (SOC) under selected fast-growing tree species in Ethiopia's Diksis district, Oromia region. Major parameters, height (H) and diameter at breast height (DBH), were measured in permanently sampled plots (9mx9m) with three replications to evaluate the biomass carbon stock of selected species. Soil samples (0–15 and 15-30 cm) were also collected to determine soil organic carbon (SOC) and bulk density. Above and below-ground biomass (AGB) and (BGB) were calculated using the site and species-specific allometric equations, and SOC was analysed using appropriate procedures in the laboratory. The results showed that the highest total biomass carbon stock was recorded for Eucalyptus globulus (5.7Mg C ha-1), and the lowest was recorded for Eucalyptus grandis (1.2 Mg C ha-1). Amongst the studied tree species, the highest and lowest mean total soil organic carbon (SOC) was recorded for Eucalyptus saligna (60 Mg C ha-1) and Eucalyptus viminalis (35.4 Mg C ha-1), respectively. The study also revealed that plantation sites could enhance carbon stock accumulation in biomass and soil organic carbon. Hence, considering that incorporating fast-growing tree species in plantations is helpful in climate change mitigation strategies is a preeminent approach beyond their economic values.

BACKGROUND: Anopheles stephensi is an emerging exotic invasive urban malaria vector in East Africa. The World Health Organization recently announced an initiative to take concerted actions to limit this vectors expansion by strengthening surveillance and control in invaded and potentially receptive territories in Africa. This study sought to determine the invasion of An. stephensi in southern Ethiopia. METHODS: A targeted entomological survey, both larvae and adult, was conducted in Hawassa City, southern Ethiopia between November 2022 and February 2023. Anopheles larvae were reared to adults for species identification. CDC light traps and BG Pro traps were used indoors and outdoors overnight at selected houses to collect adult mosquitoes in the study area. Prokopack aspirator was employed to sample indoor resting mosquitoes in the morning. Adults of An. stephensi was identified using morphological keys and then confirmed by PCR. RESULTS: Larvae of An. stephensi were found in 28 (16.6%) of the 169 potential mosquito breeding sites surveyed. Out of 548 adult female Anopheles mosquitoes reared from larvae, 234 (42.7%) were identified as An. stephensi morphologically. A total of 449 female anophelines were caught, of which 53 (12.0%) were An. stephensi. Other anopheline species collected in the study area included Anopheles gambiae sensu lato (s.l.), Anopheles pharoensis, Anopheles coustani, and Anopheles demeilloni. CONCLUSION: This study confirmed the presence of An. stephensi in southern Ethiopia. The presence of both larval and adult stages of this mosquito attests that this species established sympatric colonization with native vector species such as An. gambiae (s.l.) in southern Ethiopia. The findings warrant further investigation on the ecology, behaviour, population genetics, and role of An. stephensi in malaria transmission in Ethiopia.

The study was carried out to determine the effects of addition of Cumin (Cuminum cyminum L.), Sichuan pepper (Zanthoxylum bungeanum) or their mixture on the chemical, textural, microbial and sensory characteristics and antioxidant capacity of Camembert type cheese made from dairy goats. The chemical composition of cheese was not affected by addition of spices (Cumin, Sichuan pepper or their mixture). Addition of spices considerably affected the texture, microbial and sensory quality and antioxidant capacity of cheese. Overall acceptability score increased from 2.8 in the control cheese to 3.7, 3.2 and 3.4 in the cheeses spiced with cumin, Sichuan pepper and their mixture, respectively after 40 days of ripening. All spiced cheeses also showed higher antioxidant activity compared to the control cheese. Total phenolic content increased from 20.8 to 82.3 in the control cheese to 32.5–94.5, 46.7–118.8, 37.4–104.6 in the cheeses spiced with cumin, Sichuan pepper and their mixture, respectively during the 40 days of ripening period. Similarly, the DPPH increased from 10.4 to 60.4 in the control cheese to 16.7–73.5, 25.8–87.8, 20.3–80.7 in the cheeses spiced with cumin, Sichuan pepper and their mixture, respectively during the 40 days of ripening period. In conclusion, addition of Cumin, Sichuan pepper and their mixture produced goat milk camembert type cheese with better sensory quality and antioxidant capacity without affecting the composition of cheese.

Background. Vitamin D deficiency (VDD) is a global health concern affecting people of all ages. The Ethiopian guidelines recommend sun exposure for neonates starting from 2 weeks old, with 15 to 20 minutes per day. However, evidence suggests that the implementation of this recommendation is inconsistent. Most studies conducted in Ethiopia regarding infant sunlight exposure have been limited to health facilities and towns. Objective. this study aimed to assess mothers’ practice, and factors affecting the sunlight exposure of their infants in Adami Tulu Jido Kombolcha district, East Shoa Zone, Oromia Region, Ethiopia, 2022. Method. A community based cross-sectional study design was conducted among 575 mothers with their infant’s from March 11 to 25, 2022. A lottery method sampling technique was employed to select local administrative units and systematic random sampling employed to select study participants. Practices and knowledge were assessed by categorizing mothers based on their responses to practice and knowledge questions, respectively. Mothers who scored above the mean value of 4.5 were classified as having good practice, while those who scored 6.9 or below on the knowledge questions were classified as having poor knowledge. Data were collected through face-to-face interviews using both semi-structured and structured questionnaires. The data were then entered into EPI Data version 3.1 and exported to SPSS version 25 for analysis. The association between variables was analyzed using bivariate and multivariable binary logistic regression and level of significant determined with adjusted odd ratio at 95% CI and P -value less than

Early detection of cancer typically facilitates improved patient outcomes; however, many cancers are not easily diagnosed at an early stage. One potential route for developing new, non-invasive methods of cancer detection is by testing for cancer-related volatile organic compounds (VOCs) biomarkers in patients’ urine. In this review, 44 studies covering the use and/or identification of cancer-related VOCs were examined, including studies which examined multiple types of cancer simultaneously, as well as diverse study designs. Among these studies the most studied cancers included prostate cancer (29% of papers), lung cancer (22%), breast cancer (20%), and bladder cancer (18%), with a smaller number of studies focused on colorectal cancer, cervical cancer, skin, liver cancer and others. Importantly, most studies which produced a VOC-based model of cancer detection observed a combined sensitivity and specificity above 150%, indicating that urine-based methods of cancer detection show considerable promise as a diagnostic tool. Mass spectrometry (MS) and electronic noses (eNose) were the most employed tools used in the detection of VOCs, while animal-based models were less common. In terms of VOCs of interest, 47 chemical species identified as correlated with various types of cancer in at least two unrelated papers, some of which were consistently up- or down-regulated in cancer patients, and which may represent useful targets for future studies investing urinary VOC biomarkers of cancer. Overall, it was concluded that research in this field has shown promising results, but more work may be needed before the widespread adoption of these techniques takes place.

BackgroundDespite notable progress in the control and prevention of malaria in the Horn of Africa, the disease continues to cause significant morbidity and mortality in various regions of Ethiopia, and elsewhere in the region. The transmission of malaria is affected by genetic, sociocultural, and ecological factors. Lare is an Ethiopian district adjacent to the Ethio-South Sudan border, in Gambella region. The region currently has the highest prevalence of malaria in Ethiopia. This study assesses the burden and spatiotemporal patterns of disease transmission, including the effect of climatic factors on the occurrence of malaria, across an international border crossing. This understanding can assist in crafting informed programmatic and policy decisions for interventions.MethodsThis study was conducted in Lare district, Southwest Ethiopia, a temperate zone. A retrospective descriptive analysis was conducted using clinical service data collected between 2011 and 2021 from the 9 health facilities of the district. Both clinically diagnosed patients and those identified using microscopy and rapid diagnostic testing (RDT) were included in the study. Additionally, climate data was incorporated into analyses. Examples of analyses include malaria burden, positivity rate, incidence, species frequency, and an ANOVA to assess inter-annual case number and meteorological factor variation.ResultsBetween 2011 and 2021, a total of 96,616 suspected malaria cases were tested by microscopy or RDT, and 39,428 (40.8%) of these cases were reported as positive. There were 1276 patients admitted with 22 deaths recorded. There were further more significant fluctuations in positivity rates across years, the highest being 74.5% in 2021. Incidence varied from 18.0% in 2011 to 151.6% in 2016. The malaria parasite species most detected was Plasmodium falciparum, followed by a smaller proportion of Plasmodium vivax. The greatest proportions of P. falciparum cases were observed in 2018 and 2019, at 97.4% and 97.0% prevalence, respectively. There was significant seasonal variation in case number, the highest observed in July through September of each year. Climatic conditions of annual rainfall, temperature and humidity favored the increment of malaria cases from June until October.ConclusionThe study shows that the burden, i.e. morbidity and mortality (with fluctuating patterns) of malaria are still significant public health problems and can pose serious consequences in the district. This has implication for cross-border malaria transmission risk due to considerable border crossings. The predominant cause of the disease is P. falciparum, which causes severe complications in patients. The district has to prepare to deal with such complications for better patient care and outcomes.