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Present study was conducted to compare the indigenous, crossbred cattle and buffaloes for the utilization of nutrients, growth and methane emission when fed on a similar diet. A 120-days feeding trial was carried out with six animals each of Murrah buffalo, Vrindavani and Tharparkar cattle, each on a similar diet comprising of wheat straw 30% and concentrate 70%. The DM intake (kg/d) was significantly higher for Vrindavani cattle than Murrah buffaloes and Tharparkar cattle. Whereas, the apparent digestibility of nutrients was similar in all the groups. Average daily gain (g/d) was higher in Murrah buffaloes than Vrindavani and Tharparkar cattle. Higher feed conversion ratio was seen in Vrindavani than other two groups which indicate that the Murrah and Tharparkar have better feed efficiency than Vrindavani. The N balance was significantly higher in Murrah followed by Vrindavani and was lowest in Tharparkar. The methane emission (l/kg DMI, l/kg DDMI) was similar among the three groups. It was concluded that Vrindavani cattle showed higher feed conversion ratio than buffaloes and Tharparkar cattle, which signifies later two species are superior in nutrient utilization than former one. In terms of methane production and digestibility of nutrients, the animals of all three groups were similar.

Aims: Bordetella bronchiseptica is an etiologic agent of bronchopneumonia and progressive atrophic rhinitis (PAR) in swine. Both toxigenic and nontoxigenic B. bronchiseptica strains have been associated with bronchopneumonia. Monitoring and investigation of outbreaks involving these bacteria require sensitive and accurate identification and reliable determination of the isolates. In the present study, we report the development, optimization and performance characteristics of polymerase chain reaction (PCR) for B. bronchiseptica strains. Methodology and Results: A total of 47 isolates of B. bronchiseptica were biochemically identified from 90 pigs suffering from bronchopneumonia maintained in a semi intensive rearing system of organized piggery in Meghalaya. PCR was employed with filamentous hemagglutinin toxin genes (fhaB and fhaC) and fimbrial toxin genes (fim2 and fim3) primers to identify the specific toxin types of B. bronchiseptica. All the 47 isolates were positive for all the toxin genes. The specifity of designed primer pairs was tested by screening some common bacterial species related to the respiratory tract namely, Pasteurella multocida, Staphylococcus aureus and Streptococcus spp. No DNA amplifications of the organisms tested could be seen in the specificity test. Amplicon mobility in agarose gels indicate the amplicons are highly stable. Conclusion, significance and impact of study: The data presented, establish this PCR as a reliable method for identification and study of adhesins of B. bronchiseptica that may greatly simplify investigations of swine bronchopneumonia and PAR for Indian isolates.

A study on the neutron production from single and double gas puff Z-pinches on the CESZAR linear transformer driver with ∼0.45 MA current and 170 ns rise time is presented. Total neutron yield measurements made with a LaBr activation detector are compared for three configurations, using a double nozzle setup. When a single, hollow, deuterium gas shell was used, reliable implosions could only be attained at higher load mass than the optimal value to match implosion time with the driver rise time, with neutron yields of ∼106 per pulse. The use of a double gas puff configuration with a deuterium center jet allowed a reduction in the shell density and operation closer to machine-matched conditions, recording up to (4.1 ± 0.3) × 107 neutrons/pulse when either Kr or D2 was used in the shell. For a comparable mass and implosion time, using a higher atomic-number gas in the outer shell results in more unstable plasma surface and smaller plasma radius at the location of instability bubbles, which, however, do not seem to consistently correlate with a higher neutron yield. Comparing implosion dynamics with models and neutron yields with literature scaling suggests that the machine current is not well coupled to the plasma during the final stages of compression. Optimizing current and energy coupling to the pinched plasma is critical to improving performance, particularly in low-impedance drivers. [ABSTRACT FROM AUTHOR]

Abstract Background COVID-19 pneumonia and respiratory failure are the leading causes of death in COVID-19 patients. Prone positioning was hypothesized to improve oxygenation in ARDS patients and is being studied in COVID-19, but the current evidence is still unclear regarding survival and hospitalization. We aimed to investigate the effect of prone positioning on oxygenation in patients with COVID-19 pneumonia and ARDS and to examine the factors associated with better/worse outcomes. Methods A retrospective record-based cohort study included all confirmed COVID-19 patients with pneumonia and ARDS who underwent prone positioning admitted to King Fahad Hospital, Medina, Saudi Arabia, during 2020–2021. Results This study included 75 cases (mean age 60.3 ± 15.7 year, 50 (66.7%) males), and all fulfilled the definition of ARDS. There was a significant improvement in oxygenation (PaO2 and PaO2/FIO2) following prone positioning (53.5 ± 6.8 vs. 60.4 ± 8.2 mmHg, p

المخلص: أهداف البحث: ضائقة داء السكري هي حالة من الضائقة العاطفية التي تنشأ من العيش مع مرض مزمن وعبء التعديلات اليومية للأدوية ونمط الحياة. تدرس هذه الدراسة انتشار ضائقة داء السكري في مرضى السكري من النوع 2 في الأردن والعوامل الاجتماعية والديموغرافية والطبية. طرق البحث: استخدمنا دراسة مستعرضة مع حجم عينة يبلغ 608 مرضى سكري من النوع 2 في الأردن، بين سن 15-80 عاما. قام المشاركون بتعبئة استبيان حيث طلب منهم تقييم مقياس ضائقة داء السكري الخاص بهم. تم استبعاد 32 مشاركا وفقا لمعايير الاستبعاد، مما يؤدي إلى إدراج 576 شخصا في هذه الدراسة. النتائج: إن انتشار ضائقة داء السكري الإجمالي هو 53٪ (25٪ كمرض معتدل و 28٪ كمرض عالي)، والضائقة العاطفية هي الأعلى انتشاراً بين المقاييس الفرعية لضائقة السكري بانتشار إجمالي يبلغ 58.8٪. تظهر البيانات وجود علاقة كبيرة بين ضائقة السكري وعوامل مختلفة بما في ذلك العمر، وجود مضاعفات السكري، نوع الدواء المستخدم، والالتزام بالدواء. الاستنتاجات: أظهرت هذه الدراسة انتشارا عاليا لضائقة داء السكري (53٪) ويجب أن يساعد ذلك مقدمي الرعاية الصحية على معرفة أهمية فحص ضائقة السكري كجزء من إرشادات العلاج، خاصة في المرضى الذين يتناولون عدة أنواع من الأدوية للسكري، والمرضى الذين لديهم مضاعفات طبية سابقة متعلقة بالسكري والمرضى الذين يظهرون انخفاضا في الالتزام بالأدوية؛ وجد أنهم معرضون لخطر الإصابة بمرض السكري في هذه الدراسة. Abstract: Objectives: Diabetes distress (DD) is a state of emotional distress that evolves from living with chronic disease and the burden of daily adjustments of medications and lifestyle. This study investigated the prevalence of DD in patients with type 2 diabetes mellitus (T2DM) in Jordan and the related sociodemographic and medical factors. Methods: We conducted a cross-sectional study in 608 patients with T2DM in Jordan, ranging from ages 15 to 80 years. The participants filled out a questionnaire where they were asked to self-assess their DD using the Diabetes Distress Scale. In all, 32 participants were excluded according to the exclusion criteria, which resulted in 576 people being included in this study. Results: The overall prevalence of DD was 53% (25% had moderate distress and 28% had high distress). Emotional distress had the highest prevalence among the DD subscales, with a total prevalence of 58.8%. The data showed a significant association of DD with different factors including age, the presence of diabetic complications, the type of medication used, and medication adherence. Conclusion: This study showed a high prevalence of DD (53%). This finding should raise awareness to healthcare providers about the importance of screening for DD as part of the treatment guidelines, especially in patients who are on multiple medication regimens for DM; patients who have previous medical complications related to DM; and those who exhibit poor adherence to medications, which was found to be a risk factor of DD in this study.

The adoption of data science brings vast benefits to Small and Medium-sized Enterprises (SMEs) including business productivity, economic growth, innovation and job creation. Data science can support SMEs to optimise production processes, anticipate customers’ needs, predict machinery failures and deliver efficient smart services. Businesses can also harness the power of artificial intelligence (AI) and big data, and the smart use of digital technologies to enhance productivity and performance, paving the way for innovation. However, integrating data science decisions into an SME requires both skills and IT investments. In most cases, such expenses are beyond the means of SMEs due to their limited resources and restricted access to financing. This paper presents trends and challenges towards effective data-driven decision making for organisations based on a 3-year long study which covered more than 85 UK SMEs, mostly from the West Midlands region of England. In particular, this study attempts to find answers to several key research questions around data science and AI adoption among UK SMEs, and the advantages of digitalisation and data-driven decision making, as well as the challenges hindering their effective utilisation of these technologies. We also present two case studies that demonstrate the potential of digitisation and data science, and use these as examples to unveil challenges and showcase the wealth of currently available opportunities for SMEs.

Abstract Background Poor balance associated with increased postural sway is a risk factor for the high incidence of injuries found during specific menstrual cycle phases. This fact led to the hypothesis that female reproductive hormones affect soft tissue and neuromuscular function, reducing postural balance and resulting in a high injury prevalence among female college students. So, the current study aimed to identify the influence of ovulation in association with sex hormone variation across the menstrual cycle on postural sway in college students. Material and methods Forty female college students were enrolled in this study. They were recruited among physical therapy students at Deraya University, New Minya, Egypt. They were aged from 17 to 22 years. They were allocated to a single group. Progesterone and estradiol blood levels were measured to detect the timing of the follicular and luteal phases, and a urine luteinizing hormone (LH) strip test was used to determine when ovulation occurred. The dynamic postural sway index was assessed by using the Biodex Balance system. All measurements were taken on the early follicular (1st–3rd) day, the ovulatory (11th–13th) day, and the mid-luteal phase (21st–23rd) day from the onset of menstruation. Results Statistical analysis showed that the anteroposterior, mediolateral, and overall sway index increased significantly during the ovulatory phase compared to the earlier follicular and mid-luteal menstrual cycle phases in female college students (P 0.05). Conclusions It can be concluded that increased female sex hormones during ovulation affect postural sway, which may disturb balance and increase the risk of injuries in college students.

Abstract Background Lung cancer (LC) is one of the leading causes of death worldwide. Programmed cell death receptor 1 (PD-1) interacts with its ligand (PDL-1) on T cells inhibiting its functioning which may affect the patient's immunological response. Aim Investigate if there is a link between smoking and tissue expression of PDL-1 and vitamin D receptor (VDR) in lung cancer patients. In addition, the relation of vitamin D with smoking and these biochemical markers. Methods PDL-1 and VDR expressions were evaluated by real-time PCR in 54 lung cancer biopsy samples and 36 controls to prove this hypothesis. Vitamin D levels in the blood were measured using an ELISA. Results Expressions of PDL-1 were significantly upregulated in LC patients than in controls. The highest expression was in stage II and in squamous cell carcinoma followed by small cell carcinoma then adenocarcinoma. However, VDR expressions and vitamin D levels in serum were significantly downregulating in LC patients than in controls. There was a positive correlation between PDL-1expression and duration of smoking but not smoking index. Also, there is an inverse correlation between duration of smoking, smoking index, and VDR. Conclusion Expression of PDL-1 in LC was significantly upregulated and correlated with staging. Interestingly, our current study for the first time explained the role of duration of smoking on PDL-1 and VDR in the pathogenesis of LC. As PDL-1 expression increased with duration of smoking whereas VDR decreased, this novel findings may provide a possible link between the cumulative effect of smoking and the level of expressions of these biomarkers.

Transcatheter aortic valve implantation (TAVI) is one of the rapidly evolving treatment strategies for severe aortic stenosis. Included in this category are inoperable, high, intermediate, and low surgical risk patients. It has varying types of complications that may require urgent surgical or transcatheter interventions to prevent procedural mortality and morbidity. Coronary artery occlusion is a rare and dreaded complication of TAVI. Here, we report a 73-year-old man who was diagnosed with severe aortic stenosis and underwent transfemoral TAVI. Unfortunately, during preimplantation balloon valvuloplasty, the patient developed severe hypotension along with ischemic changes on the electrocardiographic monitor. Promptly, coronary angiography was performed which revealed complete occlusion of the left anterior descending artery secondary to embolic debris. He was successfully rescued by manual aspiration thrombectomy (MAT). MAT results in restoration of coronary flow and reversal of shock condition before completing TAVI procedure.

The adoption of data science brings vast benefits to Small and Medium-sized Enterprises (SMEs) including business productivity, economic growth, innovation and job creation. Data science can support SMEs to optimise production processes, anticipate customers' needs, predict machinery failures and deliver efficient smart services. Businesses can also harness the power of artificial intelligence (AI) and big data, and the smart use of digital technologies to enhance productivity and performance, paving the way for innovation. However, integrating data science decisions into an SME requires both skills and IT investments. In most cases, such expenses are beyond the means of SMEs due to their limited resources and restricted access to financing. This paper presents trends and challenges towards effective data-driven decision making for organisations based on a 3-year long study which covered more than 85 UK SMEs, mostly from the West Midlands region of England. In particular, this study attempts to find answers to several key research questions around data science and AI adoption among UK SMEs, and the advantages of digitalisation and data-driven decision making, as well as the challenges hindering their effective utilisation of these technologies. We also present two case studies that demonstrate the potential of digitisation and data science, and use these as examples to unveil challenges and showcase the wealth of currently available opportunities for SMEs. [ABSTRACT FROM AUTHOR]

This study attempted to explore the potential of sustainable oil palm development in South Halmahera in line with the government policies reflected in the certification scheme including the Sustainable Development Goals (SDGs) and Indonesian Sustainable Palm Oil (ISPO). This study used structural equation modelling (SEM) with partial least squares (PLS). Government, academia, a village headman, a non-government organisation and a company officer were involved in data collection. The study was carried out in 2021-2022. The results showed that the stakeholder and the company had similar social, economic, environmental and legal development priorities. Both focused on health, food security, poverty alleviation, education, gender, income, economic impact, and infrastructure. Also, both prioritised efficient natural resource use and eco-friendly technology. The stakeholders emphasised the significance of environmental conservation in achieving sustainability. On the other hand, the company prioritised addressing climate change. The findings also offered two paths to achieve sustainability based on the perspectives of the stakeholder and the company. Surprisingly, both agreed that the environment development pillar of the SDGs plays a pivotal role in attaining ISPO. [ABSTRACT FROM AUTHOR]

Z-pinch platforms constitute a promising pathway to fusion energy research. Here, we present a one-dimensional numerical study of the staged Z-pinch (SZP) concept using the FLASH and MACH2 codes. We discuss the verification of the codes using two analytical benchmarks that include Z-pinch-relevant physics, building confidence on the codes' ability to model such experiments. Then, FLASH is used to simulate two different SZP configurations: a xenon gas-puff liner (SZP1*) and a silver solid liner (SZP2). The SZP2 results are compared against previously published MACH2 results, and a new code-to-code comparison on SZP1* is presented. Using an ideal equation of state and analytical transport coefficients, FLASH yields a fuel convergence ratio (CR) of approximately 39 and a mass-averaged fuel ion temperature slightly below 1 keV for the SZP2 scheme, significantly lower than the full-physics MACH2 prediction. For the new SZP1* configuration, full-physics FLASH simulations furnish large and inherently unstable CRs (>300) but achieve fuel ion temperatures of many kilo-electron volts. While MACH2 also predicts high temperatures, the fuel stagnates at a smaller CR. The integrated code-to-code comparison reveals how magnetic insulation, heat conduction, and radiation transport affect platform performance and the feasibility of the SZP concept. [ABSTRACT FROM AUTHOR]

The ABCD rule is a simple framework that physicians, novice dermatologists and non-physicians can use to learn about the features of melanoma in its early curable stage, enhancing thereby the early detection of melanoma. Since the interpretation of the ABCD rule traits is subjective, different solutions have been proposed in literature to tackle such subjectivity and provide objective evaluations to the different traits. This paper reviews the main contributions in literature towards automating asymmetry, border irregularity, color variegation and diameter, where the different methods involved have been highlighted. This survey could serve as an essential reference for researchers interested in automating the ABCD rule.