Concentration in Knowledge Output:A Case of Economics Journals

Journals moderate knowledge activity in economics. The activity of publishing article in professional journal forms significant part of knowledge output. Output of economics articles has been growing over the time. We examine an important question: Is there any case of institutional or location concentration in knowledge production? This paper analyses concentration indicators specific to economics journals and explores link between publication process and concentration. The analysis of various concentration measures present evidence for institutional-geographic-area-author concentration in Knowledge production in Economics. High concentration levels indicate possibility of institutional lock-in. The literature provides evidence for myopic refereeing, editorial favouritism and the presence of ‘lock-in’ effect. The achievement in journal publication is influenced by factors like institutional affiliation, propitious circumstances etc. Discussion carried out in this paper hints the possibility of causal link between unfair process and unfair outcome.Knowledge,Lotka's Law,Fourier Series

Partial Characterization of Protease from the Visceral Organ Waste of Cobia (Rachycentron canadum)

Proteases are the most important enzymes accounting for approximately 60% of the total industrial enzyme market. Its isolation from the visceral organ waste of Cobia showed the highest specific activity in the 40 – 50 % ammonium sulphate precipitated sample. Hence, that fraction was dialyzed and was found to have an increase in the specific activity from 2.0 – 3.2 U/mg. Purification of the dialyzed fractions on Sephadex G-100 column also revealed an increase in the specific activity from 3.2 – 3.5 U/mg. The molecular weight of the enzyme was found to be 32.0 KDa. Zymogram was done to confirm the presence of protease. The optimum pH and temperature of the isolated enzyme was shown to be 8 and 60?C where the protease activity was found to be the highest. Keywords: Cobia, alkaline protease, fish waste, enzym

Evaluation of Barley Genotypes Against Spot Blotch Disease in Inner Tarai Region of Nepal

Spot blotch caused by Bipolaris sorokiniana (Sacc. in Sorok.) Shoem. is an important disease of barley (Hordeum vulgare L.). A total of 126 barley genotypes received from Hill Crops Research Program, Kabre, Dolakha having SoluUwa as a susceptible check and Bonus as a resistant check were evaluated as barley disease screening nursery (BDSN) under natural epiphytotic condition at National Maize Research Program, Rampur, Chitwan during winter seasons of 2017 and 2018. The nursery was planted in augmented design. The resistant and susceptible checks were repeated and planted after each 10 tested entries. The unit plot size was 2 rows of one meter length for each genotype planted continuously with 25cm row to row spacing. The seed rate was 100 kg/ha. The recommended fertilizer dose of 23:30:0 N:P2O5:K2O kg/ha was applied. The double digit scale (00 to 99) was used to measure overall foliar infection on the whole plant during flowering, soft dough and hard dough stages. Other agronomic practices were followed as per recommendation. Genotypes B86019-1K-3K-0K3, ACC 2087, ACC 2441, ACC GHv-06816, ACC 1597, ACC 1612, ACC 2059 and ACC 2032 were resistant against spot blotch disease. Similarly, 32 barley genotypes were moderately resistant and rest of the tested genotypes were susceptible to the disease. The selected resistant barley genotypes can be used in crossing program and/or promoted for further testing to develop spot blotch resistant varieties for inner Tarai region of Nepal

SPEECH RECOGNITION USING SOM AND ACTUATION VIA NETWORK IN MATLAB

This paper proposes a method of Speech recognition using Self Organizing Maps (SOM) and actuation through network in Matlab. The different words spoken by the user at client end are captured and filtered using Least Mean Square (LMS) algorithm to remove the acoustic noise. FFT is taken for the filtered voice signal. The voice spectrum is recognized using trained SOM and appropriate label is sent to server PC. The client and the server communication are established using User Datagram Protocol (UDP). Microcontroller (AT89S52) is used to control the speed of the actuator depending upon the input it receives from the client. Real-time working of the prototype system has been verified with successful speech recognition, transmission, reception and actuation via network

Using NDVI to Differentiate Wheat Genotypes Productivity Under Dryland and Irrigated Conditions

Crop breeders are looking for tools to facilitate the screening of genotypes in field trials. Remote sensing-based indices such as normalized difference vegetative index (NDVI) are sensitive to biomass and nitrogen (N) variability in crop canopies. The objectives of this study were (i) to determine if proximal sensor-based NDVI readings can differentiate the yield of winter wheat (Triticum aestivum L.) genotypes and (ii) to determine if NDVI readings can be used to classify wheat genotypes into grain yield productivity classes. This study was conducted in northeastern Colorado in 2010 and 2011. The NDVI readings were acquired weekly from March to June, during 2010 and 2011. The correlation between NDVI and grain yield was determined using Pearson’s product-moment correlation coefficient (r). The k-means clustering method was used to classify mean NDVI and mean grain yield into three classes. The overall accuracy between NDVI and yield classes was reported. The findings of this study show that, under dryland conditions, there is a reliable correlation between grain yield and NDVI at the early growing season, at the anthesis growth stage, and the mid-grain filling growth stage, as well as a poor association under irrigated conditions. Our results suggest that when the sensor is not saturated, i.e., NDVI \u3c 0.9, NDVI could assess grain yield with fair accuracy. This study demonstrated the potential of using NDVI readings as a tool to differentiate and identify superior wheat genotypes

Impacts and Risk of Generative AI Technology on Cyber Defense

Generative Artificial Intelligence (GenAI) has emerged as a powerful technology capable of autonomously producing highly realistic content in various domains, such as text, images, audio, and videos. With its potential for positive applications in creative arts, content generation, virtual assistants, and data synthesis, GenAI has garnered significant attention and adoption. However, the increasing adoption of GenAI raises concerns about its potential misuse for crafting convincing phishing emails, generating disinformation through deepfake videos, and spreading misinformation via authentic-looking social media posts, posing a new set of challenges and risks in the realm of cybersecurity. To combat the threats posed by GenAI, we propose leveraging the Cyber Kill Chain (CKC) to understand the lifecycle of cyberattacks, as a foundational model for cyber defense. This paper aims to provide a comprehensive analysis of the risk areas introduced by the offensive use of GenAI techniques in each phase of the CKC framework. We also analyze the strategies employed by threat actors and examine their utilization throughout different phases of the CKC, highlighting the implications for cyber defense. Additionally, we propose GenAI-enabled defense strategies that are both attack-aware and adaptive. These strategies encompass various techniques such as detection, deception, and adversarial training, among others, aiming to effectively mitigate the risks posed by GenAI-induced cyber threats

Factors Affecting the Productivity of Coffee in Gulmi and Arghakhanchi Districts of Nepal

Coffee is one of the major potential cash crops with lucrative export value grown in mid-hills of Nepal. Nepalese coffee production has suffered long by low productivity. Research was conducted from February to May, 2019 to analyze the factors affecting the productivity of coffee in Arghakhanchi and Gulmi districts of Nepal. These two districts were, purposively selected for this study taking account of comparative advantage and past studies recommendations for coffee sector. Altogether, 100 coffee growing households 50 from each, Arghakhanchi and Gulmi, were sampled by using multistage sampling technique. A pre-tested semi-structured interview schedule was used to collect the primary information while secondary information was collected reviewing the relevant publications. Ordinary Least Square (OLS) regression model was used to determine the factors affecting the productivity of coffee. The study revealed that the number of active family members involved in coffee production (0.000), adoption of income diversification through intercropping (0.005), training (0.072) and technical assistance (0.021) had positive and significant effect on coffee productivity. Encouraging the household to have coffee production as their primary occupation, providing technical assistance on rational land utilization and intercropping and strengthening the skill and knowledge of farmers through trainings could significantly support in increasing the productivity of coffee

Progressive hemi facial atrophy - Parry Romberg syndrome presenting as severe facial pain in a young man: a case report

We present a 30-year-old South Indian man who presented with complaints of left sided headache and facial pain for past 3 months, severe for past 10 days. On physical examination, right side of the face appeared normal. Left side of the face showed signs of hemi atrophy with minimal drooping of left eyelid. All Systems were found to be normal. Routine blood and urine investigations results were within normal limits. X-ray chest revealed no abnormalities and x-ray skull showed both sides equal. Computerized tomogram of the brain showed left minimal sub dural hygroma with no midline shift, and no evidence of cerebral edema or cerebral atrophy. Nerve conduction study showed features suggestive of trigeminal neuralgia. MRI of the skull base was also normal and showed no evidence of trigeminal nerve compression. Interestingly, he had minimal response to analgesics, steroids, and propranolol, but showed immediate response to carbamazepine. Hence this patient indeed had Parry Romberg syndrome: Hemi facial atrophy with trigeminal neuralgia

Anti-Angiogenic and Vasculoprotective Effect of Punica Granatum Root

AIM AND OBJECTIVE: Angiogenesis is a process of formation of new blood vessels from a pre-existing vasculature. It plays a vital role in embryonic development and numerous pathological conditions including cancer, rheumatoid arthritis, diabetes retinopathy, age related macular degeneration and neurological disorders such as Parkinsonism and Alzheimer‟s disease (Folkman 1990; Folkman 1995). In cancer, the growth and metastasis of tumour are dependent on angiogenesis (Hazel 2003). Cancer cells can generate various pro-angiogenic factors such VEGF, FGF, EGF. These factors promote the migration, proliferation and tube formation of endothelial cells which are essential steps for angiogenesis. The newly formed blood vessels can promote cancer growth by supplying nutrients, oxygen and most importantly facilitate cancer cell metastasis to other localities (Sassa and Hatta 2009; Homayouni 2009). In diabetic patients, hyperglycemia is the triggering factor for tissue alterations such as damage to capillary endothelial cells in the retina and BRB breakdown (Zhang et al. 2014; Brownlee 2005) and one of the key players is vascular endothelial growth factor (VEGF), which promotes angiogenesis, abnormal vascular permeability, and eventually, an inflammatory response. Thus interrupting the process of angiogenesis has become one of the promising approaches in the treatment and prevention of cancer progression and diabetic retinopathy. Drug development from natural products has become a rapidly emerging and highly promising strategy to identify novel anti-angiogenic and anti-tumour agents. Plant derived compounds have played an important role in the development of several clinically useful anticancer agents. Over 62 % of biologically active substances currently used as anticancer agents are derived from natural sources, including plants, marine organism and microorganism. Today over 300 anti-angiogenic molecules targeting different signalling pathways are being tested for their anticancer properties at preclinical and clinical stages (Sassa and Hatta, 2009; Homayouni, 2009). Although the results of clinical trials are encouraging the effects were modest (Lu and Bergers, 2013). Therefore, the search and discovery of novel anti-angiogenic principle that selectively target the angiogenic process could bring hope to millions of sufferers with cancer. Punica granatum belonging to family Punicaceae is more commonly known as pomegranate (Salgado et al. 2006). Punica granatum is a large shrub which grows 12-16 feet, has many spiny branches with lance shaped glossy leaves. The bark of the tree turns gray as the tree ages. The flowers are large, red, white, or variegated having a tubular calyx that eventually becomes the fruit. Pomegranate is considered “A pharmacy unto itself” (Jurenka 2008). Pomegranate has many potential effects including bactericidal, antifungal, antiviral, immune modulation, vermifuge, stimulant, refrigerant, astringent, stomachic, styptic, laxative, diuretic and antihelminthic. It has also been widely used in treatment of cardiovascular diseases, diabetes, diarrhea, dysentery, asthma, bronchitis, cough, bleeding disorders, fever, inflammation, acquired immune deficiency syndrome, dyspepsia, ulcers, bruises, sores, mouth lesions, skin lesions, malaria, prostate cancer, atherosclerosis, hypertension, hyper lipidemia, denture stomatitis, male infertility, vaginitis, erectile dysfunction, Alzheimer's disease, obesity, and neonatal hypoxic-ischemic brain injury (Abdollahzdeh et al 2011; Jurenka 2008; Prakash et al. 2011). Punica granatum Linn roots are found to be rich in ellagitannins, including punicalin and punicalagin, numerous piperidine alkaloids (Tanaka et al. 1986; Neuhofer 1993). They are known for antihelmintic and vermifuge properties (Naqvi et al. 1991) and were found to be effective against melanoma in mice (Suresh et al. 2012). From the literature review, it was noted that fruit extract, peel extract (Dana et al. 2015) and pomegranate juice (Tibullo et al. 2016) possessed ant-angiogenic activity and it was noted that very limited study has been carried out in roots of Punica granatum. Moreover, no scientific report is available regarding antiangiogenic and vasculoprotective potential of Punica granatum roots to the best of my knowledge. Based on this, the present study was planned to evaluate anti-angiogenic and vaculoprotective property of Punica granatum roots in chorioallantoic membrane model. SUMMARY AND CONCLUSION: The effect of punica granatum roots on angiogenesis and vasoprotection was evaluated by chorioallantoic membrance (CAM) model. Powdered Punica granatum roots were extracted with ethanol by hot continuous extraction method. The crude ethanol extract of Punica granatum was subjected to preliminary photochemical examination and quantitative analysis. The free radical scavenging activity of extract was evaluated by DPPH radical scavenging and nitric oxide scavenging activity. It was observed that the extract was rich in alkaloids, flavonoids, tannins, saponins, glycoside and possessed a potent free radical scavenging activity. The extract was screened for angiogenesis modulation in chorioallantoic membranel. In CAM model, a significant decrease in average number of blood vessels was noted in extract treated group compared to vehicle control eggs. The extract was subjected to fractionation using solvents of increasing potency and the fractions were subjected to evaluation of anti-angiogenesis activity in CAM. Among the fractions, the ethyl acetate fraction showed a potent angiogenesis inhibition compared to vehicle control. Based on these results the ethyl acetate fraction was evaluated against glucose induced vascular changed in CAM model. To induce hyperglycemia in developing embryo, a single intravitellus injection of 5 mg glucose/g whole egg was introduced. The treatment groups received ethyl acetate fraction and 5 mg glucose/g whole egg. On day 12 of incubation, the blood glucose levels were measured in blood samples taken from CAM vessels and vascular changes were examined in CAM. Hyperglycaemia with vascular leakage, haemorrhagic spots (microaneurysms), proliferation of new vessels (neovascularization), superficial lesions were spotted in untreated eggs. Ethyl acetate fraction 100 μg showed a significant protection against glucose induced microvascular abnormalities with a significant decrease in blood glucose level and reduced average number of blood vessels. These findings demonstrate the anti-angiogenic and vasculoprotective effect of Punica granatum against hyperglycaemia induced vascular changes in CAM model. In conclusion, root extract of Punica granatum possess a significant angiogenesis inhibition in chorioallantoic membrane assay and vasuloprotective effect in glucose induced vascular change. The possible mechanism of antiangiogenesis and vasoprotective actions are might be due to the presence of active principles that possess a potent antioxidant property of roots, as antioxidants are potent inhibitors of angiogenesis and might be due to the presence of inhibitors that repress the expression of VEGF and VEGF like growth factors thereby inhibiting the formation of new blood vessels and maintaining a vascular stability by inhibiting capillary degeneration and permeability. Thus the isolation of antiangiogenic active principle from Punica granatum roots could bring hope to millions of sufferers with cancer and diabetic retinopathy. Further work is in progress to identify the bioactive compounds and delineate the underlying mechanism of antiangiogenesis and vasoprotection

A Temporal Anomaly Detection System for Vehicles utilizing Functional Working Groups and Sensor Channels

A modern vehicle fitted with sensors, actuators, and Electronic Control Units (ECUs) can be divided into several operational subsystems called Functional Working Groups (FWGs). Examples of these FWGs include the engine system, transmission, fuel system, brakes, etc. Each FWG has associated sensor-channels that gauge vehicular operating conditions. This data rich environment is conducive to the development of Predictive Maintenance (PdM) technologies. Undercutting various PdM technologies is the need for robust anomaly detection models that can identify events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal vehicular operational behavior. In this paper, we introduce the Vehicle Performance, Reliability, and Operations (VePRO) dataset and use it to create a multi-phased approach to anomaly detection. Utilizing Temporal Convolution Networks (TCN), our anomaly detection system can achieve 96% detection accuracy and accurately predicts 91% of true anomalies. The performance of our anomaly detection system improves when sensor channels from multiple FWGs are utilized