This study was conducted at the Patuakhali Science and Technology University Veterinary Clinic, Babugonj, Barisal during the period from January 2008 to December 2011 to report the four years clinical diseases of ruminants. A total of 1241 clinical cases (793 cattle and 448 goats) were recorded and analyzed. Diagnosis of each of the clinical cases was made on clinical history, clinical signs, and faecal examination for parasitic cases. The clinical cases were primarily categorized into three major groups, namely, (1) Medicinal, (2) Gynaeco-obstetrical and (3) Surgical cases. Medicinal cases constituted highest percentage (cattle 84.1% and goats 81.0%) in comparison to gynaeco-obstetrical (cattle 4.7% and goats 1.1%) and surgical (cattle 11.2% and goats 17.9%) cases. Among the medicinal cases in cattle, highest percentage of cases was recorded with parasitic diseases (50.4%), followed by general systemic states (14.8%) and digestive disorders (14.2%). Other cases were respiratory disorders (5.5%), infectious diseases (4.6%), skin conditions (3.4%), eye disease (3.1%), urogenital disorders (1.5%), metabolic diseases (1.3%) and musculo-skeletal disorders (0.9%). In case of goats, the highest cases was recorded with digestive disorders (22.9%), followed by parasitic diseases (20.4%) and respiratory disorders (16.8%). Other Medicinal cases in goats were eye diseases (13.5%), infectious diseases (11.8%), general systemic states (9.6%), musculo-skeletal disorder (3.3%), skin diseases (0.8%) and nutritional deficiency diseases (0.8%). Among the gynaeco-obstetrical cases, anestrus (59.5%) in cattle and metritis (40.0%) in goats were recognized as the major gynaeco-obstetric problems. Traumatic wounds (cattle - 52.8%, goat - 28.8%) and castration (31.3%) in goats were recognized as the main disorders which required surgical interventions. It may be concluded that a number of diseases with various percentages have been occurring in the Babugonj upazila and this report will help to prioritize any control measures against major disease conditions reported in this study. However, it is required to estimate the prevalence of diseases in the population of that upazila to have more comprehensive information on the diseases of cattle and goat.DOI: http://dx.doi.org/10.3329/bjvm.v10i1-2.15648

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As of March 2021, the SARS-CoV-2 virus has been responsible for over 115 million cases of COVID-19 worldwide, resulting in over 2.5 million deaths. As the virus spread exponentially, so did its media coverage, resulting in a proliferation of conflicting information on social media platforms—a so-called “infodemic.” In this viewpoint, we survey past literature investigating the role of automated accounts, or “bots,” in spreading such misinformation, drawing connections to the COVID-19 pandemic. We also review strategies used by bots to spread (mis)information and examine the potential origins of bots. We conclude by conducting and presenting a secondary analysis of data sets of known bots in which we find that up to 66% of bots are discussing COVID-19. The proliferation of COVID-19 (mis)information by bots, coupled with human susceptibility to believing and sharing misinformation, may well impact the course of the pandemic.

Identification of risk factors is important for the design of control programmes for mastitis in cows. Information about farms and management was collected at a farm visit. California Mastitis Test (CMT) was performed to assess sub-clinical mastitis, and cows, udder and milk were examined for clinical mastitis. A total of 347 lactating cows from 83 farms in the dry season (November -February) and 388 lactating cows from 89 farms in the wet season (June -October) were studied. The overall prevalence of mastitis was 19.9% and 44.8% in dry and wet seasons, respectively. The prevalence of mild mastitis was 17.3% and 40.7%, whereas that of moderate mastitis was 2.6% and 4.1% in dry and wet seasons, respectively. The prevalence of mastitis was higher (P<0.01) in wet than in dry season. On average, 18.7% quarters had mastitis during the wet season and 6.9% in the dry season. In the dry and wet seasons, respectively, 63.9% and 11.2% had completely dry floors, and the prevalence of mastitis was 22.6% and 30.0%. On the other hand, 88.8% and 36.1% of 83 farms had partly or completely wet and soiled floor and the prevalence of mastitis was 40.0% and 59.5% in the dry and wet seasons, respectively. Udder cleanliness, milk yield and peri-parturient diseases significantly (P<0.01) increased the risk of mastitis. The prevalence of mastitis is regarded as quite high. Dry and clean floor to keep cow's udder and teat clean would help control mastitis in the dairy farms of

Irreversible logic circuits dissipate heat for every bit of information that is lost. Information is lost when the input vector cannot be recovered from its corresponding output vector. Reversible logic circuit naturally takes care of heating because it implements only the functions that have one-to-one mapping between its input and output vectors. Therefore reversible logic design becomes one of the promising research directions in low power dissipating circuit design in the past few years and has found its application in low power CMOS design, digital signal processing and nanotechnology. This paper presents the efficient approaches for designing reversible fast adders that implement carry look-ahead and carry-skip logic. The proposed 16-bit high speed reversible adder will include IG gates for the realization of its basic building block. The IG gate is universal in the sense that it can be used to synthesize any arbitrary Booleanfunctions. The IG gate is parity preserving, that is, the parity of the inputs matches the parity of the outputs. It allows any fault that affects no more than a single signal readily detectable at the circuit's primary outputs. Therefore, the proposed high speed adders will have the inherent opportunity of detecting errors in its output side. It has also been demonstrated that the proposed design offers less hardware complexity and is efficient in terms of gate count, garbage outputs and constant inputs than the existing counterparts.