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Abstract Background/Objectives Childhood obesity, particularly in girls, is linked to early puberty onset, heightening risks for adult-onset diseases. Addressing childhood obesity and precocious puberty is vital to mitigate societal burdens. Despite existing costly and invasive medical interventions, introducing lifestyle-based alternatives is essential. Our study investigates alternate-day fasting’s (ADF) impact on pubertal development in normal-weight and high-fat diet (HFD)-induced obese female mice. Methods Four groups of female mice were utilized, with dams initially fed control chow during and before pregnancy. Post-parturition, two groups continued on control chow, while two switched to an HFD. Offspring diets mirrored maternal exposure. One control and one HFD group were subjected to ADF. Morphometry and hormone analyses at various time points were performed. Results Our findings demonstrate that ADF in normal-weight mice led to reduced body length, weight, uterine, and ovarian weights, accompanied by delayed puberty and lower levels of sex hormones and growth hormone (GH). Remarkably, GH treatment effectively prevented ADF-induced growth reduction but did not prevent delayed puberty. Conversely, an HFD increased body length, induced obesity and precocious puberty, and altered sex hormones and leptin levels, which were counteracted by ADF regimen. Our data indicate ADF’s potential in managing childhood obesity and precocious puberty. Conclusions ADF reduced GH and sex hormone levels, contributing to reduced growth and delayed puberty, respectively. Therefore, parents of normal-weight children should be cautious about prolonged overnight fasting. ADF prevented HFD-induced obesity and precocious puberty, offering an alternative to medical approaches; nevertheless, further studies are needed for translation into clinical practice.

Background and Aim: Coccidiosis, caused by protozoan parasites of the genus Eimeria, is a significant concern in poultry farming, leading to substantial economic losses worldwide. In Pakistan, poultry is a major component of the agricultural sector, with both broiler and egg-laying chickens playing crucial roles in meeting the country’s protein needs. Despite the importance of the poultry industry, there is limited data on prevalence and species distribution of Eimeria in different types of chickens in District Swabi, Khyber Pakhtunkhwa, Pakistan. This study aims to estimate the prevalence and determine the distribution of Eimeria species in broiler and egg-laying chickens in this region. Materials and Methods: Nine hundred fecal samples were collected from broiler (380) and egg-laying domestic chickens (520) in District Swabi, Pakistan. Microscopic analysis was used to identify Eimeria parasites in all samples. After microscopic examination for positive identification, Eimeria species were determined using polymerase chain reaction (PCR) assays. Results: Microscopic examination identified Eimeria oocysts in 44.4% (400/900) of the samples. Eimeria parasite infection significantly varied based on chicken type, age, and gender (p < 0.05). The study found that broiler chickens (52.63%, 235/450), young chickens (4–6 weeks) (55.5%, 285/500), and females (52.2%, 200/380) were more infected with Eimeria spp. than egg-laying domestic chickens (38.5%, 200/520), adults (above 6 weeks) (28.8%), and males (36.7%, 165/450). PCR indicated a distribution rate of 42.5% (170/400) Eimeria tenella, 26.25% (105/400) Eimeria acervulina, 20% (80/400) Eimeria maxima, and 11.25% (45/400) Eimeria mitis. None of Eimeria necatrix, Eimeria brunetti, or Eimeria praecox was found in the study. Conclusion: This study underlines the essential requirement for targeted interventions due to the prevalence and predominance of E. tenella among identified Eimeria species. Future research should focus on refined sampling strategies and investigate the clinical significance of these parasites for effective disease management in the local poultry industry.

Background and Aim: Trypanosomiasis, a parasitic infection caused by various Trypanosoma species, poses a significant threat to global livestock, affecting both human health and economic sectors. This study aimed to estimate the prevalence of Trypanosoma evansi in Southern Punjab, Pakistan, focusing on key ruminant species, including camels, cattle, buffaloes, goats, and sheep. Materials and Methods: A total of 240 blood samples, comprising 48 samples from each animal species (camel, cattle, buffaloes, goat, and sheep) were collected from three districts in Southern Punjab. The collected samples were subjected to thin smear microscopy, DNA extraction, and polymerase chain reaction (PCR) amplification. The molecular characterization was conducted using the TBR primer set, which targeted repeated satellite DNA regions and the cytochrome oxidase II gene of T. evansi. Results: About 22.08% (53/240) of overall samples were positive for trypanosomiasis, with prevalence rates being 23.75% (19/80), 21.25% (17/80), and 21.75% (17/80) for districts Muzaffargarh, Lodhran, and Bahawalpur, respectively. 5.83% (14/240) of samples tested for T. evansi using PCR were positive in the districts of Muzaffargarh 7.50% (6/80), Lodhran 5.00% (4/80), and Bahawalpur 5.00% (4/80). Among the animals tested, camels had the highest positivity rate. The microscopic examination confirmed infection rates of 45.83% (22/48) for camels, 18.75% (9/48) for cattle, 8.33% (4/48) for buffaloes, 18.75% (9/48) for goats, and 18.75% (9/48) for sheep (p < 0.001). PCR results did not reveal substantial differences (p < 0.05) in prevalence: camels 12.50% (6/48), cattle 6.25% (3/48), buffaloes 0% (0/48), goats 8.33% (4/48), sheep 2.08% (1/48); while distinct disparities were detected district-wise: Muzaffargarh 23.75% (19/80), Lodhran 21.25% (17/80), and Bahawalpur 21.25% (17/80). The PCR results for these districts were insignificantly different: 7.50% (6/80), 5% (4/80), and 5% (4/80). The microscopic infection rate in camels from Bahawalpur was 56.30% (9/16). The microscopic analysis in Buffaloes reported a 6.30% (1/16) infection rate, but PCR results indicated no infections (0%) in any district. A significant difference (p < 0.001) in identifying Trypanosoma species was found between positively and negatively tested animals in both microscopic and PCR methods. Conclusion: This study emphasizes the necessity of regularly using PCR-based screening for its superior sensitivity and specificity over traditional microscopy. The varying occurrence of trypanosomiasis among districts reflects the intricate nature of this diseases epidemiology in the region. Reducing economic losses from trypanosomiasis in Southern Punjab, Pakistan, requires targeted interventions, such as vector control measures and farmer education.

Background and Aim: Bluetongue is a vector-borne, emerging disease that poses a severe threat to most domesticated animals. A cross-sectional study was conducted to estimate the prevalence of bluetongue virus (BTV) disease in apparently healthy sheep and goats in Kalat, Balochistan. Materials and Methods: A total of 270 serum samples (sheep: 150 and goat: 120) were collected and screened for the detection of anti-BTV antibodies using a competitive enzyme-linked immunosorbent assay. The data regarding different contributory risk factors were also collected using a predesigned questionnaire. Results: It revealed that overall, 27.4% (74/270, 95% confidence interval, χ2 = 1.71, p = 0.12) prevalence in both sheep and goat populations. The highest prevalence of 47% (32/68) was recorded in Surab city with the lowest prevalence of 15.49% (11/71) in the Manguchar area. In contrast, in Kalat 28.1% (9/32), Daan area 24% (12/50), and Marap area 22.44% (11/49), seropositivity was recorded. Upon sex bases, antibodies were almost equally found in both male 28.57% (8/28) and female 27.27% (66/242) animal populations. Moreover, all four breeds (Balochi, Khurasani, Lehri, and Rakhshani) were equally and potentially seropositive. The Khurasani breed was the most susceptible to 34.69% (17/49), followed by the Balochi breed, 45/145 (31%) seropositivity. The prevalence of BTV was 16.66% (1/6) in Rakhshani breed and 15.71% (11/70) in Lehri breed., Ticks were found in almost 21% of animals, while 93% of animals were reared on open grazing in rangelands. Conclusion: This study clearly indicates widespread BTV infection in small ruminants in the study area that may pose serious threats to livestock farming. Further extensive studies are recommended to study the prevalence of disease in different agroecological zones of the province. This also warns the high-ups to manage concrete efforts to eradicate and control the disease in the area.

Rhipicephalus sanguineus can complete up to four generations per year, depending on factors such as climate and host availability. Biomorphic studies of R. sanguineus were conducted under laboratory conditions. The larval, nymphal and adult ticks were fed on sheep at 250C, 60 % relative humidity (RH) and exposed to daylight. The incubation period was lasted 35 days. The average mean of premoulting and moulting period of larvae was 70 ± 0.91 and 7.4 ± 0.6 days, respectively. The time durations of premoulting and moulting of nymphs were 62 ± 1.66 and 13 ± 6.4 days, respectively. The average developmental periods were 6.09, and 5.15 days for larval pre-feeding, and feeding, respectively. The average developmental periods were 3.54, and 6.11 days for nymphal pre-feeding, and feeding, respectively. The complete life cycle of R. sanguineus was 180 days with range of 120-286 days. The average weights of the unfed larvae, and nymphs were 0.04 ± 0.03, and 0.40 ± 0.09 mg, respectively while 0.60 ± 0.05, and 5.02 ± 0.20 mg for engorged larvae and nymphs, respectively. The index of reproduction efficiency (REI), egg production efficiency (EPE), and the index of reproductive fitness (RFI) averaged 14.99 ± 3.65, 0.31 ± 0.08, and 11.74 ± 3.01, respectively. Scutum length and width of male was 2.2 and 1.2mm, respectively while length and width of female was 1.04 and 0.99 mm, respectively. The current study findings could help the workers in adopting different management studies for ticks in the world.

Animal production is highly affected due to ticks and diseases caused by ticks. Tick control is critical for the economic well-being of the animal industry. This study focused on anti-tick properties of the Neem, Azadirachta indica extracts against Rhipicephalus sanguineus in vitro conditions. R. sanguineus exhibited a high (P < 0.05) dose revolting reaction to A. indica. There were no significant differences in reaction magnanimity between both sexes. The essence also prominently (p < 0.05) retarded the shedding of 60 % of R. sanguineus engorged nymphs. It resulted in that mortality percentage increasing with an increase in the dose of A. indica. At 20 % of A. indica, 87.76 % of tick mortality was recorded, while 53.23 % at 15% concentration. Probit analysis showed a repellent EC50 of A. indica for male and female ticks was 4.87, and 4.87 mg/mL, respectively. The findings advocate to A. indica is potent enough to use for anti-tick action. Further studies are needed to test Neem extract on other developmental stages i.e. eggs, nymphs, and larvae of tick.

Cadmium sulfide and zinc oxide nanoparticles were prepared, characterized and used as electrode modifiers for the sensing of two non-steroidal anti-inflammatory drugs (NSAIDs): naproxen and mobic. The structural and morphological characterization of the synthesized nanoparticles was carried out by XRD, UV-Vis spectroscopy, FTIR and scanning electron microscopy. The electrode’s enhanced surface area facilitated the signal amplification of the selected NSAIDs. The CdS-modified glassy carbon electrode (GCE) enhanced the electro-oxidation signals of naproxen to four times that of the bare GCE, while the ZnO-modified GCE led to a two-fold enhancement in the electro-oxidation signals of mobic. The oxidation of both NSAIDs occurred in a pH-dependent manner, suggesting the involvement of protons in their electron transfer reactions. The experimental conditions for the sensing of naproxen and mobic were optimized and, under optimized conditions, the modified electrode surface demonstrated the qualities of sensitivity and selectivity, and a fast responsiveness to the target NSAIDs.

Abstract Herein, we report the synthesis, characterization, and application of TiO2/ZnO and La-doped ZnO nanocomposites for the detection and degradation studies of Malachite Green (MG). TiO2/ZnO and La-doped ZnO nanocomposites were synthesized by reflux and hydrothermal methods, respectively, and characterized by UV–visible spectroscopy, X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, and energy-dispersive X-ray analysis. A glassy carbon electrode modified with COOH-fMWCNTs and TiO2/ZnO nanocomposite demonstrated high sensitivity characteristics for the sensing of MG up to 0.34 nM limit of detection. The application of a photocatalytic method using 2% La-doped ZnO led to 99% degradation of MG in 40 min. The photocatalytic breakdown of MG followed first-order kinetics as revealed from the spectroscopic and electrochemical monitoring of the degradation process. Color variation offered naked-eye evidence of MG degradation in the specified time. The experimental findings helped in proposing the degradation mechanism. To the best of our knowledge, the current work presents the first example of a novel photocatalyst for almost absolute degradation of MG. Moreover, the electrode modifier as well as the approach adopted is novel and efficient for minute-level detection of MG and monitoring of its photocatalytic degradation.

Structural, electronic, optical and elastic properties of Silver based Perovskite AgXCl3 (X = Ca, Sr) are studied by utilizing wien2k package with in DFT. The structural investigation reveals their stability and shows that these compounds are cubic with space group pm-3m 221. For electronic properties the band structure and density of states are computed which indicates the semiconducting nature of both compounds. Elastic constants, Pugh’s ratio, bulk modulus, Poisson’s ratio and anisotropy factor are studied for the analysis of elastic characteristic. The Pugh’s ratio describes the ductile nature of the compounds and ionic nature is determined from the evaluated Cauchy pressure. Optical parameters such as dielectric function, extinction coefficient, refractive index, absorption coefficient, reflectivity and optical conductivity are calculated in the energy range of 0 eV–35 eV. The thermal stability is conformed from the thermal property. The study of these compounds reveals that they can be potential candidates for optoelectronic devices.

Background: The SARS-COV-2's spread from continent to the continent has resulted in an increased number of mutations in the viral gene encoding proteins. As a result, mutations in target proteins provide a significant challenge in creating antiviral drugs and vaccines. The present review discussed the COVID-19 epidemiology and the effects of drugs being tested against COVID-19/SARS-COV-2. Dosage of these drugs along with associated challenges was also discussed. Methodology: Systematic review was conducted after a thorough search in the "PubMed, NIH, Elsevier, Scopus, Web of Science, Science Direct, and Google Scholar database. 45 studies on drugs associated with COVID-19 fulfilled the inclusion criteria and were selected for this review. Results: The FDA only accepted the Remdesivir drug against SARS-COV-2, as the hospitalized patients recovered very quickly by taking it. Antiviral EIDD-2801 has been found to make the SARS-COV-2 unable to infect cells by causing genetic modifications in the virus RNA. Similarly, Nitazoxanide appeared beneficial against SARS-COV-2 in a primary intervention and severe conditions (including pregnancy) without undesirable effects on the newborns. Children with mild cases can be handled solely by proper caring. Conclusion: Although Remdesivir and Dexamethasone are recommended in severe cases, clinical trials are ongoing to investigate other possible therapies like MAb and Convalescent Plasma antibodies for COVID-19. Older drugs (usually used to treat other conditions) are also under-tested by researchers to see if they are effective for COVID-19. Further tests are essential to validate whether any of the mentioned above possible therapies would be helpful for COVID-19 treatment.

A theoretical study on Rb-based fluorperovskites RbXF3(X = Rh, Os, Ir) is performed for the first time to explore their structural, electronic, optical and thermoelectric properties. The compounds are stable in cubic perovskite type structures with lattice spacing in the range of 4.30 4.35 Å. RbRhF3 and RbIrF3 exhibit half-metallic character with indirect band gaps of 4.2 eV and 2.1 eV, respectively, at R-Γ, whereas RbOsF3 possesses entirely semiconducting nature. The calculation of elastic properties revealed that under study compounds are mechanically stable, having ionic bonding. Furthermore, all compounds show ductile nature. Optical properties were also calculated in the broad energy range 0–40 eV.

Cadmium sulphide (CdS) nanoparticles (NPs) were synthesized through hydrothermal route and characterized by UV-Vis spectroscopy, X-ray diffraction (XRD), Energy dispersive X-ray analysis, Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy and Thermo gravimetric analysis (TGA).The band gap of CdS nanoparticles was found to be 2.38 eV. CdS NPs are crystalline aggregates with hexagonal structure as shown by SEM and XRD analysis. TGA study revealed that the synthesized nanomaterials were very stable to temperature and only 6.54% total loss occurred during heating range (25 °C–600 °C).The CdS NPs were used for the first time against the degradation of Eosin B (EB) and Methyl green (MG) dyes in aqueous solution.The degradation of EB and MG over CdS nanocatalysts followed second order kinetics. The predicted activation energies for both the dyes' reactions were 61.1 kJ/mol and 32.11 kJ/mol, respectively. About 95% and 90% dye degradation was observed at the time interval of 160 minutes for EB and MG, respectively. High percent degradation of EB was observed at high pH (pH 0) while at low pH (pH 4) high percent degradation was found for MG dye. Maximum dye degradation was found at the optimal dose (0.03 g/L) of the catalyst and at low dye concentration. The rate of EB and MG dye degradation was found to increase with increase in temperature up to 45 °C. The recyclability study showed that CdS nanoparticles could be reused for the degradation of the given dyes. Good antibacterial activity against Staphylococcus aureus was shown by CdS NPs. From the biocompatibility it was confirmed that CdS NPS are bioincompatible compatible. HIGHLIGHTS The band gap was 2.38 eV.; Dyes degradation over followed second order kinetics.; 61.1 kJ/mol and 32.11 kJ/mol were activation energies.; 95% and 90% dye degradation was observed for EB and MG, respectively.; Good antibacterial activity against Staphylococcus aureus.; CdS NPS were found bioincompatible compatible.;

This research aimed to identify how libraries promote their services and resources for awareness creation among library patrons and the role of the library staff in creating this awareness among users about information services and resources. The study was undertaken through a questionnaire-based survey. Data collection procedures were completed in two phases. In the first round, the data were collected from 13 in-charge librarians/ marketing officers and in the second round, data were collected from 243 library users. Data were analyzed using SPSS. Results demonstrate that planning and implementing promotional activities provide a chance to evaluate the utilization of information resources and services. Promotional activities not only create awareness but also justify the budget spent on the acquisition of information resources.

Objective: To analyze the risk factors for pulmonary embolism stationed at high altitudes with high altitude as one of the determinants. Study Design: Retrospective longitudinal study. Place and Duration of Study: Combined Military Hospital Skardu Pakistan, from Jan 2016 to Jan 2020. Methodology: A total of 25 consecutive cases with pulmonary embolism reported to this hospital during the study period were enrolled. Medical records of all patients were retrospectively analyzed to determine the risk factors. In addition, patient demographic data, clinical features, and laboratory and radiological findings were recorded. Results: Mean age of the patient was 30.68±5.37 years with a range from 23 to 40 years, the mean height of deployment was 17223.00±3577.00 feet, while the mean duration of stay was 53.92±44.76 days. Dyspnoea (84%) was the commonest clinical presentation followed by palpitation, chest pain, headache and haemoptysis. Most patients (88%) were non-smokers, while no patient had known significant risk factors. Thrombophilia and vascultitic screening were negative for all patients. In the absence of any significant hereditary or acquired risk factor, high altitude remains the only thrombogenic risk factor patients deployed at heights. Conclusion: Stay at a high altitude is a major risk factor for pulmonary embolism in young patients without any other known risk factor.

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world’s most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public–private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

Staphylococcus aureus is a prominent cause of food-borne diseases worldwide. Enterotoxigenic strains of this bacteria are frequently found in raw milk, and some of these strains are resistant to antimicrobials, posing a risk to consumers. The main objectives of this study were to determine the antimicrobial resistance pattern of S. aureus in raw milk and to detect the presence of mecA and tetK genes in it. A total of 150 milk samples were obtained aseptically from lactating cattle, including Holstein Friesian, Achai, and Jersey breeds, maintained at different dairy farms. The milk samples were checked for the presence of S. aureus, and it was detected in 55 (37%) of them. The presence of S. aureus was verified by culturing on selective media, gram staining, and performing coagulase and catalase tests. Further confirmation was performed through PCR with a species-specific thermonuclease (nuc) gene. Antimicrobial susceptibility testing of the confirmed S. aureus was then determined by using the Kirby–Bauer disc diffusion technique. Out of the 55 confirmed S. aureus isolates, 11 were determined to be multidrug-resistant (MDR). The highest resistance was found to penicillin (100%) and oxacillin (100%), followed by tetracycline (72.72%), amikacin (27.27%), sulfamethoxazole/trimethoprim (18.18%), tobramycin (18.18%), and gentamycin (9.09%). Amoxicillin and ciprofloxacin were found to be susceptible (100%). Out of 11 MDR S. aureus isolates, the methicillin resistance gene (mecA) was detected in 9 isolates, while the tetracycline resistance gene (tetK) was found in 7 isolates. The presence of these methicillin- and tetracycline-resistant strains in raw milk poses a major risk to public health, as they can cause food poisoning outbreaks that can spread rapidly through populations. Our study concludes that out of nine empirically used antibiotics, amoxicillin, ciprofloxacin, and gentamicin were highly effective against S. aureus compared to penicillin, oxacillin, and tetracycline.

The current research has aimed to investigate and develop machine-learning approaches by using the data in the dataset to be applied to classify location-based social network data and predict user activities based on the nature of various locations (such as entertainment). The analysis of user activities and behavior from location-based social network data is often based on venue types, which require the input of data into various categories. This has previously been done through a tedious and time-consuming manual method. Therefore, we proposed a novel approach of using machine-learning models to extract these venue categories. In this study, we used a Weibo dataset as the main source of research and analyzed machine-learning methods for more efficient implementation. We proposed four models based on well-known machine-learning techniques, including the generalized linear model, logistic regression, deep learning, and gradient-boosted trees. We designed, tested, and evaluated these models. We then used various assessment metrics, such as the Receiver Operating Characteristic or Area Under the Curve, Accuracy, Recall, Precision, F-score, and Sensitivity, to show how well these methods performed. We discovered that the proposed machine-learning models are capable of accurately classifying the data, with deep learning outperforming the other models with 99% accuracy, followed by gradient-boosted tree with 98% and 93%, generalized linear model with 90% and 85%, and logistic regression with 86% and 91%, for multiclass distributions and single class predictions, respectively. We classified the data using our machine-learning models into the 10 classes we used in our previous study and predicted tourist destinations among the data to demonstrate the effectiveness of using machine learning for location-based social network data analysis, which is vital for the development of smart city environments in the current technological era.

We consider the recent challenges of 3D shape analysis based on a volumetric CNN that requires a huge computational power. This high-cost approach forces to reduce the volume resolutions when applying 3D CNN on volumetric data. In this context, we propose a multiorientation volumetric deep neural network (MV-DNN) for 3D object classification with octree generating low-cost volumetric features. In comparison to conventional octree representations, we propose to limit the octree partition to a certain depth to reserve all leaf octants with sparsity features. This allows for improved learning of complex 3D features and increased prediction of object labels at both low and high resolutions. Our auxiliary learning approach predicts object classes based on the subvolume parts of a 3D object that improve the classification accuracy compared to other existing 3D volumetric CNN methods. In addition, the influence of views and depths of the 3D model on the classification performance is investigated through extensive experiments applied to the ModelNet40 database. Our deep learning framework runs significantly faster and consumes less memory than full voxel representations and demonstrate the effectiveness of our octree-based auxiliary learning approach for exploring high resolution 3D models. Experimental results reveal the superiority of our MV-DNN that achieves better classification accuracy compared to state-of-art methods on two public databases.

Green parks in urban areas are believed to enhance the well-being of residents. The importance of green spaces to support health and fitness in urban areas has recently regained interest. Reports released in 2010-2016 by the World Health Organization (WHO) on urban planning, environment, and health stated that green spaces can have a positive impact on physical activity, social and mental well-being, enhance air quality and decrease noise exposure. We analyzed the number of check-ins in various parks of Shanghai by utilizing geotagged social media network check-in data. This article presents a descriptive study using social media data by obtaining the three-year comparison of spatial and temporal patterns of park visits to raise public awareness that green parks provide a healthy environment that can be beneficial for the well-being of urban citizens. We investigated the visitor spatiotemporal behavior in more than 115 green parks in 10 districts of Shanghai with approximately 250,000 check-ins. We examined 3 years of geotagged data and our main findings are: (i) the spatial and temporal variations of users in urban green parks (ii) the gender differences in space and time with relation to urban green parks. The main objective of this article is to present evident data for policymakers on the advantages of providing green spaces access to urban citizens and to facilitate cities with systematic approaches to provide green space access to improve the health of urban citizens.

BackgroundCryptosporidium spp. is recognized as an opportunistic zoonotic parasite that infects humans as well as wild and domestic animals. This enteric protozoan is a major cause of diarrhea in humans and animals and often result in death due to severe dehydration. The present study was designed to investigate the prevalence, identification of various risk factors and evaluation of sensitivity of the two diagnostic techniques for rapid and correct detection of Cryptosporidium infection in diarrheic sheep in Pakistan.MethodsA total of 360 fecal samples were collected and processed for detection of Cryptosporidium infection after proper preservation. These samples were properly stained with modified Ziehl-Neelsen acid staining and then examined under simple microscope at 100x magnification for confirmation of Cryptosporidium oocysts. The same samples were again processed through simple PCR for confirmation of the Cryptosporidium spp.ResultsThe age wise prevalence was detected through simple microscopy and PCR. We found highest prevalence at the age of ≤1 year followed by 1-2 years of age while the lowest prevalence was recorded at the age of ≥ 2-3 years of sheep and found significant difference between different ages (PConclusionIt was concluded that molecular detection is the most efficient, specific and sensitive technique for detection of Cryptosporidium infection than simple microscopy. Moreover sheep is the major potential source of infection to other wild and domestic animals including humans.

It is well known fact that fixed point results are very useful for finding the solution of different types of differential equations. In this paper, some new results of multi-valued functions involving rational inequality in G−metric spaces have been obtained. Some of the new concepts are also defined over G−metric spaces that are open set, interior of set, and limit point of set. Moreover, we have presented the application of our main results in the field of Homotopy. Some non-trivial examples are also provided to discuss the validation of the main finding.

An efficient and reliable electrochemical sensing platform based on COOH-fMWCNTs modified GCE (COOH-fMWCNTs/GCE) was designed for the detection of nanomolar concentration of Nile Blue Sulphate (NBS). In comparison to the bare GCE, the electrochemical sensing scaffold considerably enhanced the peak current response of NBS dye as confirmed from the results of voltammetric investigations. The electrochemical approach of detecting NBS in the droplet of its solution dried over the surface of modified electrode validated, the role of modifier in enhancing the sensing response. Under optimized conditions, the designed electrochemical platform demonstrated a wide linearity range (0.03–10 μM) for NBS, with LOD of 1.21 nM. Moreover, COOH-fMWCNTs/GCE was found reproducible and stable as confirmed by repeatability and inter-day durability tests. The selectivity of the designed sensing matrix was ensured by anti-interference tests. The photocatalytic degradation of NBS dye was carried out by using TiO2 nanoparticles as photocatalyst in the presence of H2O2. UV-visible spectroscopic studies revealed 95% photocatalytic degradation of NBS following a pseudo-first-order kinetics with a rate constant of 0.028 min−1. These findings were supported electrochemically by monitoring the photocatalytically degraded dye at the designed sensing platform. The color variation and final decolorization of the selected dye in water served as a visual indicator of the degradation process. To conclude, the designed sensing platform immobilized with COOH-fMWCNTs imparted improved selectivity and sensitivity to detect and to, monitor the photocatalytic degradation of NBS.

Nanoparticles typically have dimensions of less than 100 nm. Scientists around the world have recently become interested in nanotechnology because of its potential applications in a wide range of fields, including catalysis, gas sensing, renewable energy, electronics, medicine, diagnostics, medication delivery, cosmetics, the construction industry, and the food industry. The sizes and forms of nanoparticles (NPs) are the primary determinants of their properties. Nanoparticles’ unique characteristics may be explored for use in electronics (transistors, LEDs, reusable catalysts), energy (oil recovery), medicine (imaging, tumor detection, drug administration), and more. For the aforementioned applications, the synthesis of nanoparticles with an appropriate size, structure, monodispersity, and morphology is essential. New procedures have been developed in nanotechnology that are safe for the environment and can be used to reliably create nanoparticles and nanomaterials. This research aims to illustrate top-down and bottom-up strategies for nanomaterial production, and numerous characterization methodologies, nanoparticle features, and sector-specific applications of nanotechnology.

Bovine babesiosis (BB) is a vector-borne disease (VBD) that affects cattle in tropical and subtropical areas, caused by the haemoprotozoa Babesia bovis and Babesia bigemina. It is transmitted by tick bites belonging to the genus Rhipicephalus and is clinically characterized by high fever, depression, anorexia, decreased milk and meat production, haemoglobinemia, haemoglobinuria, jaundice, and pregnancy loss. In this study, the propagation of B. bigemina was evaluated by intraperitoneally inoculating 3 × 106 red blood cells infected with B. bigemina into rabbits. The study showed that variations in rabbit body temperatures are related to induced bovine babesiosis. A significant increase in temperature (39.20 ± 0.23 °C) was observed from day 4 onwards, with the maximum temperature (40.80 ± 1.01 °C) on day 9 post-inoculation. This study included susceptible cross-bred calves for in vivo attenuation, and they were compared with an infected group. The calves in the infected group showed a significant increase in temperature (38.79 ± 0.03 °C) from day 3 onwards and a maximum temperature (41.3 ± 0.17 °C) on day 11. Inoculated calves showed a gradual rise in temperature post-inoculation, but the difference was not significant. Inoculated calves did not show parasitaemia, whereas 32% of infected calves displayed parasitaemia. As compared to inoculated calves post-inoculation, packed cell volume (PCV) decreased (16.36 ± 1.30) for infected calves. However, there were statistically significant differences (p ≤ 0.05) in temperatures, parasitaemia, and PCV in both inoculated and infected calves. The current study aimed to attenuate B. bigemina in rabbit models and evaluate the pathogenic potential of this organism in naive calves. In conclusion, B. bigemina proliferation was attenuated in rabbits. The rabbit model can be used to study B. bigemina in vivo in order to reduce its pathogenicity.

Zinc oxide and Fe doped zinc Oxide nanoparticles were prepared by green biosynthesis route using natural extract of Myrtus communis L as an effective chelating agent. The synthesized nanoparticles were characterized by Ultraviolet visible (UV–Visible), Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), Energy dispersive x-ray (EDX), Thermogravimetric analysis (TGA) and X-Ray diffraction (XRD) spectroscopic techniques. Antioxidant assays, free radical scavenging assays and hemolysis assays of the synthesized nanoparticles were also carried out for finding their therapeutic applications. The optical band gaps was calculated to be Eg = 3.4 eV and Eg = 3.2 eV for ZnO and Fe-ZnO nanoparticles respectively. Functional groups present in both NPs were confirmed by FTIR spectroscopy. Average particles size of pure ZnO and Fe doped ZnO nanoparticles was 21 nm and 17 nm respectively calculated from XRD pattern. SEM analysis showed that ZnO nanoparticles are granular size and have irregular spherical morphology while with Fe doping there is dispersion of nanoparticles with less agglomeration as well as regular distribution of ZnO NPs. EDX spectra indicate purification of undoped and Fe-ZnO NPs. TGA results showed that 27.8% and 10.4% weight loss occurred for ZnO and Fe-ZnO respectively at the temperature range of 30–600 °C. Doping with Fe content the photoluminescence (PL) intensity of the visible peaks of ZnO decreased. The degradation of Acid Yellow-3 over ZnO and Fe-ZnO NPs follows first order kinetics. The characterized nanoparticles were used as photo catalyst in the degradation of Acid Yellow-3 dye in aqueous solution under UV light illumination. Effect of different parameters i.e. irradiation time, initial dye concentration, catalyst dosage and temperature was also studied. The maximum degradation of dye at time of 120 min, concentration of 10 ppm, catalyst loading was 0.03 g and temperature was 50 °C. Excellent antioxidant potential was shown by the prepared NPs. Good hemolytic activity was shown by undoped ZnO NPs and good antibacterial activity by doped ZnO nanoparticles.

Objective: High ambient temperature in poultry is a challenging and fatal stress among environmental factors. It affects the production quality, damages the liver, and increases mortality in broilers. The present study is focused to explore appropriate utilization of Selenium (Se) as a feed additive in broiler chickens against high temperature. Materials and Methods: Day-old male broiler chickens (Ross 308) (n = 200) were grouped according to the supplements used in their basal diets such as: corn-soybean basal diet as control (Con), a basal diet containing sodium selenite, basal diet with probiotics, and a basal diet containing selenium-enriched probiotics (SP). At the end of the experimental period of 42 days, the liver was isolated and was used to determine the antioxidant capacity through a spectrophotometer. Inflammatory and anti-inflammatory cytokines production in the liver was measured through a real-time polymerase chain reaction. Results: Hepatic analyses revealed the decreased level of malondialdehyde, whereas glutathione, glutathione peroxidase (GSH-Px), and superoxide dismutase levels were increased in the SP group. Furthermore, supplementation of SP significantly up-regulated the mRNA expression of glutathione peroxidase 1 (GPx1), GPx4, IL6, and IL10 and down-regulated the expression of pro-inflammatory cytokines. Conclusion: It is thus concluded that SP as a potential nutritive supplement may facilitate hepatic protection by suppressing hepatic oxidation, inflammation, and necrosis during the high ambient temperature of summer. [J Adv Vet Anim Res 2019; 6(3.000): 355-361]

The social media has become an integral part of our lives with the introduction of 3G, 4G technology in Pakistan it has become possible for people to stay connected from anywhere any time. The purpose of this study is to find out that if any relationship between social media marketing and consumer buying behavior exist if their existence affected each other in any significant way. For this purpose an online survey was conducted and 100 people responded who were active users of social media in the region of Peshawar an unstructured/ structured questionnaire was designed to collect information from the respondents. The research findings and results confirms that there is a positive relationship between social media marketing and consumer buying behavior as well as that social media can be used as an effective marketing tool in region of Peshawar.

The aim of present study was to find the influence of organic selenium (Se) on blood progesterone, metabolites and milk production in Achai dairy cows. A total of 45 cows were divided into three groups. One of these was control group. The 2nd and 3rd group were supplemented with yeast based Se at the rate of 0.3 and 0.4 mg/kg dry matter intake (DMI) respectively from the start of eighth month of pregnancy until parturition. Animals supplemented with organic Se at the rate of 0.3 and 0.4 mg/kg had significantly (p

This study examines market efficiency in the light of the simple moving average technical trading rules on daily closing share prices of 100 companies listed on Pakistan Stock Exchange over ten years from 2006 to 2015. The results show strong support for simple moving average rules having both predictability and profitability for PSX. It refers that the returns from these rules are not same as investors earn from a naïve buy and hold strategy. The uses of these simple moving average rules produce abnormal returns to investors and hence nullify the weak form of efficiency on PSX.

Abstract Background Drought is a lifestyle disease. Plant metabolomics has been exercised for understanding the fine-tuning of the potential pathways to surmount the adverse effects of drought stress. A broad spectrum of morphological and metabolic responses from seven Triticeae species including wild types with different drought tolerance/susceptibility level was investigated under control and water scarcity conditions. Results Significant morphological parameters measured were root length, surface area, average root diameter and overall root development. Principal Component Analysis, Partial Least-Squares-Discriminant Analysis and Hierarchical Cluster Analysis were applied to the metabolomic data obtained by Gas Chromatography-Mass Spectrometry technique in order to determine the important metabolites of the drought tolerance across seven different Triticeae species. The metabolites showing significant accumulation under the drought stress were considered as the key metabolites and correlated with potential biochemical pathways, enzymes or gene locations for a better understanding of the tolerance mechanisms. In all tested species, 45 significantly active metabolites with possible roles in drought stress were identified. Twenty-one metabolites out of forty-five including sugars, amino acids, organic acids and low molecular weight compounds increased in both leaf and root samples of TR39477, IG132864 and Bolal under the drought stress, contrasting to TTD-22, Tosunbey, Ligustica and Meyeri samples. Three metabolites including succinate, aspartate and trehalose were selected for further genome analysis due to their increased levels in TR39477, IG132864, and Bolal upon drought stress treatment as well as their significant role in energy producing biochemical pathways. Conclusion These results demonstrated that the genotypes with high drought tolerance skills, especially wild emmer wheat, have a great potential to be a genetic model system for experiments aiming to validate metabolomics–genomics networks.

The main purpose of this research is to study the effect of various types of venues on the density distribution of residents and model check-in data from a Location-Based Social Network for the city of Shanghai, China by using combination of multiple temporal, spatial and visualization techniques by classifying users’ check-ins into different venue categories. This article investigates the use of Weibo for big data analysis and its efficiency in various categories instead of manually collected datasets, by exploring the relation between time, frequency, place and category of check-in based on location characteristics and their contributions. The data used in this research was acquired from a famous Chinese microblogs called Weibo, which was preprocessed to get the most significant and relevant attributes for the current study and transformed into Geographical Information Systems format, analyzed and, finally, presented with the help of graphs, tables and heat maps. The Kernel Density Estimation was used for spatial analysis. The venue categorization was based on nature of the physical locations within the city by comparing the name of venue extracted from Weibo dataset with the function such as education for schools or shopping for malls and so on. The results of usage patterns from hours to days, venue categories and frequency distribution into these categories as well as the density of check-in within the Shanghai and contribution of each venue category in its diversity are thoroughly demonstrated, uncovering interesting spatio-temporal patterns including frequency and density of users from different venues at different time intervals, and significance of using geo-data from Weibo to study human behavior in variety of studies like education, tourism and city dynamics based on location-based social networks. Our findings uncover various aspects of activity patterns in human behavior, the significance of venue classes and its effects in Shanghai, which can be applied in pattern analysis, recommendation systems and other interactive applications for these classes.

In this work TiO _2 , Holmium doped (Ho-TiO _2 ) Titanium oxide nanoparticles (NPs) and the corresponding nanostructured combinations (Ho-TiO _2 /ZnO NC) were successfully synthesized through sol gel method and reflux techniques respectively. The prepared nano materials were characterized with the help of x-ray diffraction Analysis (XRD), UV–visible spectroscopy, Scanning Electron Microscopy (SEM), Energy dispersive x-ray Analysis (EDX) and Fourier Transform infrared spectroscopy (FT-IR). The absorption spectra of nano materials were used for band gaps calculation. The band gap of pure TiO _2 NPs was found to be 3.10 eV which was effectively tuned to 2.65 eV by the doping of Holmium at different concentrations. XRD patterns confirmed the crystalline nature and purity of the synthesized nano materials. Morphology and elemental composition of the material were investigated using SEM and EDX respectively. FTIR helped in detecting the functional groups and grafting of the dye on the surface of nanoparticles. The nano materials were used as Photo-anodes in dye sensitized solar cells (DSSC). Pyrocatechol Violet dye was used as a photo-sensitizer. P3HT (polymer), a hole conducting polymer, was employed as a solid state electrolyte. I–V measurements were used for characterization of fabricated solar cells. Ho-TiO _2 /ZnO nanomaterial photosensitized with Pyrocatechol violet dye gave the highest percentage efficiency of 1.51. Other characteristic parameters of the fabricated devices such as short circuit current (Jsc), open circuit voltage (Voc), maximum power point (Mpp) and fill factor were found to be 11.2 mA cm ^−2 , 0.41 V, 1.55(mW cm ^−2 ) and 0.33 respectively.

The aim of this study is to analyze and compare the patterns of behavior of tourists and residents from Location-Based Social Network (LBSN) data in Shanghai, China using various spatiotemporal analysis techniques at different venue categories. The paper presents the applications of location-based social network’s data by exploring the patterns in check-ins over a period of six months. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data is translated into the Geographical Information Systems (GIS) format, and compared with the help of temporal statistical analysis and kernel density estimation. The venue classification is done by using information regarding the nature of physical locations. The findings reveal that the spatial activities of tourists are more concentrated as compared to those of residents, particularly in downtown, while the residents also visited suburban areas and the temporal activities of tourists varied significantly while the residents’ activities showed relatively stable behavior. These results can be applied in destination management, urban planning, and smart city development.

The aim of the current study is to analyze and extract the useful patterns from Location-Based Social Network (LBSN) data in Shanghai, China, using different temporal and spatial analysis techniques, along with specific check-in venue categories. This article explores the applications of LBSN data by examining the association between time, frequency of check-ins, and venue classes, based on users’ check-in behavior and the city’s characteristics. The information regarding venue classes is created and categorized by using the nature of physical locations. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data are translated into the Geographical Information Systems (GIS) format, and after analysis the results are presented in the form of statistical graphs, tables, and spatial heatmaps. SPSS is used for temporal analysis, and Kernel Density Estimation (KDE) is applied based on users’ check-ins with the help of ArcMap and OpenStreetMap for spatial analysis. The findings show various patterns, including more frequent use of LBSN while visiting entertainment and shopping locations, a substantial number of check-ins from educational institutions, and that the density extends to suburban areas mainly because of educational institutions and residential areas. Through analytical results, the usage patterns based on hours of the day, days of the week, and for an entire six months, including by gender, venue category, and frequency distribution of the classes, as well as check-in density all over Shanghai city, are thoroughly demonstrated.

Green parks are vital public spaces and play a major role in urban living and well-being. Research on the attractiveness of green parks often relies on traditional techniques, such as questionnaires and in-situ surveys, but these methods are typically insignificant in scale, time-consuming, and expensive, with less transferable results and only site-specific outcomes. This article presents an investigative study that uses location-based social network (LBSN) data to collect spatial and temporal patterns of park visits in Shanghai metropolitan city. During the period from July 2016 to June 2017 in Shanghai, China, we analyzed the spatiotemporal behavior of park visitors for 157 green parks and conducted empirical research on the impacts of green spaces on the public’s behavior in Shanghai. Our main findings show (i) the check-in distribution of users in different green spaces; (ii) the seasonal effects on the public’s behavior toward green spaces; (iii) changes in the number of users based on the hour of the day, the intervals of the day (morning, afternoon, evening), and the day of the week; (iv) interesting user behavior variations that depend on temperature effects; and (v) gender-based differences in the number of green park visitors. These results can be used for the purpose of urban city planning for green spaces by accounting for the preferences of visitors.

Modern organic electronic and power electronic devices gained attention due their superior performance and efficiency with reduced cost. While nanocomposites of these organic semiconductors have high potential to further enhance these properties. In this work, thin films of zinc oxide-polyaniline (ZnO-PANI) nanocomposite with different compositions of ZnO (50, 60 and 70 wt%) are deposited by spin coater onto the surface of p-Si. The phase identification of the samples is identified through x-ray diffraction analysis. Pure ZnO showed wurtzite crystalline while PANI and nanocomposites of ZnO-PANI showed amorphous structure. The optical absorption band gap was evaluated from Ultraviolet–visible spectroscopy absorption studies and band gaps were calculated from Tauc’s plots. The Ultraviolet–visible spectroscopy showed that by increasing ZnO content in the nanocomposite, the band gap increases from 3.25 eV to 3.3 eV and 3.4 eV for 50–50, 60–40 and 70–30 wt% respectively. The AC electrical properties of the nanocomposites were studied by using impedance spectroscopy. The parameters extracted from the impedance plots and conductivity values showed that 50–50 wt% is more conductive while that of 70%–30% wt is more resistive.

Introduction: Problematic over usage of smartphones has led to various deteriorating effects including poor sleep quality. Screen exposure, especially near bedtime, directly leads to poor sleep quality. We aimed to measure smartphone screen-time (ST) statistics of the participants directly using a smartphone application. Furthermore, we aimed to assess sleep quality using the Pittsburgh sleep quality index (PSQI), and to investigate the association between ST & PSQI. Material and Methods: This descriptive cohort study was conducted among 280 students of MBBS at Rawalpindi Medical University for a period of 1 month (30 days). Physically healthy students who owned Android smartphones were included in the study. Students with diagnosed sleep disorders and students taking sleep medication were excluded from the study. ST was recorded using a smartphone application. Sleep quality was assessed at the end of 30 days using the PSQI questionnaire. Data entry and analysis was done using SPSS v23.0. Results: Total and mean ST were calculated for every participant. The mean screen time of 242 individuals was 147.50±51.09 hours. The mean PSQI score was 6.68±2.3. 65.70% of the participants had a poor sleep quality (PSQI>5). Pearson’s correlation revealed that long total ST was associated with decreased sleep quality (R=0.356, p