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With the growing importance of entrepreneurship education, entrepreneurship programs established within higher education institutions are thriving hard to achieve entrepreneurship educational outcomes in recent years. Several studies reported the role of higher education institutions in promoting entrepreneurship education and enhancing students' skill sets in various ways. To extend this knowledge, this paper aims to analyse the role of higher education institutions in promoting innovativeness and passion among students pursuing entrepreneurship education. A meta-analytic review is conducted by combining the results from empirical analysis of 24 related studies. The influence of higher education institutions on entrepreneurship educational outcomes and individual transformations is examined and their relationships are exposed. The results of the review show that various components of higher education institutions are positively related to individual transformations (r[subscript c] = 0.579) and entrepreneurship educational outcomes (r[subscript c] = 0.331). It is also found that the passion (r[subscript c] = 0.31) and innovativeness (r[subscript c] = 0.2771) are positively correlated with entrepreneurship educational outcome. Moreover, institutional environment has a greater impact on passion (r[subscript c] = 0.531). Thus, the results indicate that higher education institutions play an important role in promoting passion and innovativeness among students.

PURPOSE: The COVID-19 pandemic and the digital transformation have hastened the demand for enterprises to be more flexible and adaptive in a fast-changing environment, making agile leadership a prominent business trend. Agile leadership improves innovation efficiency, employee performance, and team effectiveness. However, there is limited research on agile leadership’s effects on organizational outcomes. Thus, this study provides a meta-analytic review of the impact of agile leadership on organizational outcomes that cover various common dimensions like operational, employee, customer, financial, and social environments. METHODOLOGY: The study has two phases: the first phase performs bibliometric literature analysis, and the second phase performs meta-analysis. In the bibliometric literature analysis, 74 articles that were published between 2004 and 2023 were identified from Scopus and Google Scholar, and their type of publication, year of publication, countries involved in agile leadership research, keywords involved, and their association are examined. For the meta-analysis, 24 articles that performed empirical research were chosen from which the various independent and dependent variables studies, along with their standard regression coefficients (𝛽) and correlation coefficients (𝛾) that represent the relationship between agile leadership or agile leaders and that of other factors, were extracted and examined. FINDINGS: The study found that there was a significant rise in publications on agile leadership after 2020, and Turkey, the United States, and Indonesia were involved more than other countries. Moreover, agile leadership is studied more in terms of operational outcomes and employee outcomes. The results of the meta-analysis indicate that agile leadership has a strong relationship with factors like interpersonal trust (𝛽=0.93), organizational performance (𝛽=0.90), organizational effectiveness (𝛽=0.89), individual career success (𝛽=0.89) and innovation management (𝛽=0.81). Thus, it is clear that agile leadership has a stronger impact on operational outcomes than employee outcomes. Agile leadership characteristics such as digital innovation, trust, competency, result orientation, and wisdom are significant for organizational growth, team collaboration, team effectiveness, and organizational innovation. IMPLICATIONS: Identifying agile leadership concepts helps assess the progress of empirical research, improve leadership theories and models, and identify potential growth opportunities. The success of agile leadership depends on factors like a company’s culture, industry, and size, and this can be studied further. Furthermore, organizations may need to adjust their strategies on customer service, financial management, and investment so that they better reflect the values of agile leadership. ORIGINALITY AND VALUE: This study classifies numerous different research models that shed light on the efficiency of agile leadership based on a comprehensive literature review that serves as the basis for this study. In addition, this study identifies potential problem areas that need to be fixed, and as a result, it makes a contribution to the research on agile leadership.

Appropriate knowledge and expertise of parenteral injection is vital in the medical field. Hence we impart training on mannequins before the students practice on patients. This study was conducted to evaluate the skill exhibited by the students in parenteral injection skills, namely intravenous, intramuscular, intradermal and subcutaneous injections. The students were assessed for step based on the pre-validated check list created for Objective Structured Practical Examination. In this study, 16 % of the students failed to check the prescription order before starting the procedure. The name and the expiry date of the drug was not checked by 22 % of the students. Hundred percent of the students sterilized their hands. Loading of drug was done properly by 80 % of the students and 88 % of the students checked for air bubbles in the syringe and removed them properly. The site for injection was not sterilized by 26 percent of the students. Tourniquet was not applied by 19 percent of the students and 28 % of the students did not hold the bevel up during insertion for intravenous route. The steps where frequent faltering happened needs to be emphasized for them to perform better in a more efficient manner during the summative assessment as well as for future practice.

Considering natural compounds for the antiviral effect is another opportunity for exploring novel drug candidates for severe acute respiratory syndrome coronavirus 2. The selected natural compounds were interacted using a molecular docking approach. The 3D structures of the main protease and papain-like protease were used for the virtual screening to detect the potent inhibitor against SARS-CoV-2. The top-scored compounds were further analyzed for absorption, digestion, metabolism, excretion, and toxicity properties and density functional theory analysis. Our results indicated that glycyrrhizin exhibited better docking scores of -9.5 kcal/mol with main protease and -9.7 kcal/mol with papain-like protease. Next to glycyrrhizin, rutin showed a better docking score of -9.1 kcal/mol and -9.2 kcal/mol with 3-chymotrypsin-like and papain-like proteases. Violaxanthin and naringin occupied the subsequent position in the docking score table with 3CL and PL proteases, respectively. In addition, the crucial properties like drug likeliness and pharmacokinetics of the compounds were determined. There is no significant toxicity identified.

Genetic variations in the receptor, metabolizing enzymes and transporters may explain a part of the variation in anti-emetic response to ondansetron among cancer patients. This study assesses the role of ABCB1 genetic polymorphisms in the anti-emetic efficacy of ondansetron-based medication for cisplatin-based chemotherapy in South Indian cancer patients.

Purpose – The study aims at assessing the effect of digital employee experience on organisational performance, particularly in the telecommunications sector in the Sultanate of Oman, using quantitative and qualitative analysis. Research methodology – The techniques used in this empirical research include scientific literature analysis, correlation analysis, multiple regression, and sentiment analysis. Findings – The results indicate that organisational performance has a higher association with elements of the digital employee experience like work environment, organisational culture, training availability, technology accessibility, digital tool usability, and leadership support and is statistically significant at the 5% level. Also, 80% of respondents were favourable or indifferent about their digital experience. Research limitations – The study exclusively covers Oman’s telecoms industry and six important digital employee experience elements, so additional factors and industries may be examined further. A direct interview may improve findings since self-reported responses from individuals with demanding work schedules may be biased. Practical implications – Telecommunication companies must increase their efforts to engage employees in the use of digital tools and encourage their employees to utilise the different digital technologies. Originality/Value – The study investigated the six elements of the digital experience of telecom employees and its impact on organisational performance with multiple regression and sentiment analysis.

Purpose: Inherited retinal dystrophies (IRD) are a heterogeneous group of retinal diseases leading to progressive loss of photoreceptors through apoptosis. Retinitis pigmentosa (RP) is considered the most common form of IRD. Panel-based testing in RP has proven effective in identifying the causative genetic mutations in 70% and 80% of the patients. This is a retrospective, observational, single-center study of 107 RP patients who had undergone next-generation sequencing-based targeted gene panel testing for IRD genes. These patients were inspected for common phenotypic features to arrive at meaningful genotype–phenotype correlation. Methods: Patients underwent complete ophthalmic examination, and blood was collected from the proband for DNA extraction after documenting the pedigree. Targeted Next Generation Sequencing (NGS) was done by panel-based testing for IRD genes followed by co-segregation analysis wherever applicable. Results: Of the 107 patients, 72 patients had pathogenic mutations. The mean age of onset of symptoms was 14 ± 12 years (range: 5–55). Mean (Best Corrected Visual Acuity) BCVA was 6/48 (0.9 logMAR) (range 0.0–3.0). At presentation, over one-third of eyes had BCVA worse than 6/60 (

Background: India carries the largest national burden for rabies globally. Coordinating large-scale canine rabies elimination programs is challenging, particularly in rural areas, where the majority of human rabies deaths occur. This study evaluated the feasibility of combining canine rabies vaccination with pre-existing animal-health interventions or public health programs in a rural area of India. Materials and Methods: Canine rabies vaccination teams collaborated with a bi-annual bovine foot-and-mouth vaccination program coordinated by the Animal Husbandry Department (AH-collaboration) and with a village health program by the Public Health Department (PH-collaboration) in Nilgiris, Tamil Nadu, to vaccinate dogs during the implementation of these government-led health initiatives. Results: A total of 251 dogs were vaccinated over 7 days during the AH-collaboration, and 1083 dogs were vaccinated over 15 days during the PH-collaboration. The AH-collaboration achieved a vaccination coverage of 76% based on same-time sighting survey, and 58% based on post-vaccination survey. The PH-collaboration achieved vaccination coverage of 79% based on the same-time survey and 83% based on the post-vaccination survey. Conclusions: The integration of mass dog vaccination into existing government sector initiatives may facilitate the scaling up of canine rabies vaccination campaigns.

Drug repurposing refers to finding new indications for existing drugs. The paradigm shift from traditional drug discovery to drug repurposing is driven by the fact that new drug pipelines are getting dried up because of mounting Research & Development (R&D) costs, long timeline for new drug development, low success rate for new molecular entities, regulatory hurdles coupled with revenue loss from patent expiry and competition from generics. Anaemic drug pipelines along with increasing demand for newer effective, cheaper, safer drugs and unmet medical needs call for new strategies of drug discovery and, drug repurposing seems to be a promising avenue for such endeavours. Drug repurposing strategies have progressed over years from simple serendipitous observations to more complex computational methods in parallel with our ever-growing knowledge on drugs, diseases, protein targets and signalling pathways but still the knowledge is far from complete. Repurposed drugs too have to face many obstacles, although lesser than new drugs, before being successful.

Purpose: Stickler syndrome is associated with the development of rhegmatogenous retinal detachment (RRD), and often presents with ocular, auditory, skeletal, and orofacial abnormalities. Molecular analysis has proven effective in diagnosis, confirmation and classification of the disease. We aimed to describe the utility of next-generation sequencing (NGS) in genetic analysis of four Indian families with suspected Stickler syndrome. Methods: The index cases presented with retinal detachment with family history. Genetic analysis in the index case was performed by next-generation sequencing of inherited retinal degeneration genes, and validated by Sanger sequencing followed by co-segregation analysis in the other family members. Results: Twenty patients were included for the genetic analysis (15 males and 5 females from four families). Clinical details were available for 15 patients (30 eyes). Fourteen eyes (11 patients) developed RRD. In the 16 eyes without RRD, 8 underwent barrage laser to lattice degeneration and 8 were under observation. Disease segregating heterozygous mutations with pathogenic/likely pathogenic effect was identified in COL2A1 (c.4318-1G>A, c.141G>A, c.1221+1G>A for 3 families) and COL11A1 (c.1737+1 G>A for 1 family) gene. In addition to the mutation in the COL2A1 gene, a pathogenic heterozygous variant associated with risk for arrhythmogenic right ventricular cardiomyopathy (ARVC) was identified in one member. Conclusion: NGS testing confirmed the presence of the causative gene for Stickler syndrome in the index case followed by evaluation of family members and confirmation of genetic and ocular findings. We believe that this may be the first such report of families with RRD from India.

Hyperspectral data are a curse with huge dimensionality, high redundancy of spectral information, and are noisy in nature. Hundreds of narrow adjacent bands are present in HS (Hyperspectral) data with high spectral information and it always leads to a computational complexity in space and time. The information theoretic methods are used for hyperspectral band selection to avoid computational complexity. In order to address this issue, the new fusion of Mutual Information (MI) with Otsu (MI_Otsu) threshold method is proposed for hyperspectral band selection by employing three different entropy measures such as joint, conditional, and relative. The proposed approach identifies the probabilities, entropy, and mutual information between two hyperspectral bands. The optimal threshold is obtained using Otsu multi-threshold technique and highly informative bands will be selected. In addition, the SVM (Support Vector Machine) classification technique is adapted for further classification of selected bands to analyze the performance of the proposed algorithm. The experimental analysis is carried out using the real-time dataset from the test site ‘Indian Pines’ in Northwestern Indiana recorded by AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) sensor that demonstrates the effectiveness of this proposed approach. It is proved that the proposed work shows the competitive performance even with less selected bands and the relative MI_Otsu method shows a higher accuracy of 92.16% with the comparison of joint and conditional MI_Otsu.

The rise of cyber-physical-social systems (CPSS) as a novel paradigm has revolutionized the relationship among humans, computers and physical environment. The key technologies to design CPSS directly related to multi-disciplinary technologies including cyber-physical systems (CPS) and cyber-social systems (CSS). Unfortunately, the design of CPSS is not an easier process because of the network heterogeneity, complex hardware and software entities. At the same time, fog computing is emerged as an expansion of cloud computing which efficiently addresses the abovementioned issue. Resource provisioning is a main technology involved in fog computing. This paper devises a novel fuzzy clustering with flower pollination algorithm called FCM-FPA as a resource provisioning model for fog computing. At the earlier stage, the resource attributes are standardized and normalized. Next, the fuzzy clustering with FPA is developed for partitioning the resources and the scalability of resource searching has been minimized. At last, the presented resource provisioning algorithm based on optimized fuzzy clustering has been devised. The performance of the proposed FCM-FPA model has been tested using a set of two benchmark Iris and Wine dataset. The experimental outcome ensured that the FCM-FPA model has shown proficient results over the compared methods by offering maximum user satisfaction and effective resource provisioning.

Background: Chronic Renal Disease (CRD) complications had a sizeable effect on the patients. This study evaluates illness perception, treatment adherence and clinical outcomes of patients with End-Stage Renal Disease (ESRD) and finds an association with variables. Materials and Methods: A descriptive cross-sectional study was conducted among patients at Sri Ramachandra Institute of Higher Education and Research, Chennai, India during October and November 2017. Data were collected through interviews of each patient separately before hemodialysis. Demographic, clinical variables, identity dimension and control dimension of patients were assessed. Adherence behaviours were measured using ESRD-AQ in four dimensions. Clinical outcome was evaluated based on biochemical parameters. The collected data were analysed by percentage distribution and regression analysis. Results: The study had 120 patients with ESRD with male to female ratio of 2:1 where the majority (35.80%) were in the age group of 51–60. The identity dimension mean (SD) score was 10.80 (1.51). Under the control dimension mean scores were higher in the sub-dimension of emotional representations, consequences and personal control. Among 120 patients, 63 (52.50%) had adherence to dietary restriction. A statistically significant association was observed between timeline with Body Mass Index (BMI) (F3 = 4.81, p = 0.003) and comorbidity (F2 = 2.99, p = 0.022). Conclusions: The higher mean score in the sub-dimensions of emotional representations indicates a higher degree of emotional distress due to low adherence to prescribed medications.

Introduction: Nonadherence and poor health care behaviors contribute to worsening of heart failure symptoms, in many cases leading to increased morbidity and mortality. Aim: To assess the efficacy of nurse-led cardiac rehabilitation on health care behaviours in adults with chronic heart failure. Method. An experimental design was conducted in India from January to December of 2019. A sample size of 200 adults with heart failure from a tertiary cardiac care center was enrolled. Participants were allocated into an intervention group (n = 100) and a control group (n = 100). A nurse-led cardiac rehabilitation program using a virtual educational video and reminder telephone calls was given to the intervention group for six months. A modified heart failure adherence and health care behaviours scale was used. Results: 78% of the adults in the intervention group and 79% of the adults in the control group were males. 43% of the adults in the intervention group and 32% of the adults in the control group had ≥2 years of chronic heart failure. 42.27% of the participants in the intervention group and 35.05% of the adults in the control group indicated that medical follow-ups were essential. 21.65% of the adults in the intervention group and 13.40% of the adults in the control group expressed no difficulty adhering to the sodium restriction in the posttest2. The participants in the intervention group had higher health care behaviours compared to control group, p

The Mobile Ad-hoc Networks (MANETs) are often visible to the exposed terminal problem and hidden terminal problem, which exist due to non-transitivity in media access control schemes. This affects the utilization of channel and throughput in media access control protocols, e.g., dual busy tone multiple access protocol (DBTMA). Hence, to improve the fairness and throughput performance of the DBTMA it is very necessary to address the problems associated with hidden and exposed terminals. Hence, in this paper, the quality of service (QoS) is improved by enhancing the capability of the DBTMA for better network service in the MANETs. The proposed method uses an improved DBTMA called Retransmission Dual Busy Tone Multiple Access (RDBTMA) protocol. This is based on two elements namely: busy tones and Ready To Send/Clear to Send (RTS/CTS) dialogues. In addition to this fast retransmission, a strategy is used further to improve its effectiveness. The retransmission strategy is adopted using negative acknowledgment after the collision occurred by the hidden nodes. A hidden node, where the collision occurs at access point, listens to the NACK signal and uses the signal to determine the requirement fast retransmission scheme. The proposed method is simulated and compared against existing methods in terms of various network parameters. The results show that the proposed RDBTMA protocol is effective in terms of the improved QoS in terms of network throughput (21.9%), packet delivery ratio (17.8%), 14.9% less packet loss, and 38% less route discovery delay than the existing methods.

Privacy preserving is critical in the field of where data mining is transformed into cooperative task among individuals. In data mining, clustering algorithms are most skilled and frequently used frameworks. In this paper, we propose a privacy-preserving threshold clustering that uses code based technique with threshold estimation for sharing of secret data in privacy-preserving mechanism. The process includes code based methodology which enables the information to be partitioned into numerous shares and handled independently at various servers. The proposed method takes less number of iterations in comparison with existing methods that does not require any trust among the clients or servers. The paper additionally provides experimental results on security and computational efficiency of proposed method.

With the growing importance of entrepreneurship education, entrepreneurship programs established within higher education institutions are thriving hard to achieve entrepreneurship educational outcomes in recent years. Several studies reported the role of higher education institutions in promoting entrepreneurship education and enhancing students' skill sets in various ways. To extend this knowledge, this paper aims to analyse the role of higher education institutions in promoting innovativeness and passion among students pursuing entrepreneurship education. A meta-analytic review is conducted by combining the results from empirical analysis of 24 related studies. The influence of higher education institutions on entrepreneurship educational outcomes and individual transformations is examined and their relationships are exposed. The results of the review show that various components of higher education institutions are positively related to individual transformations (rc=0.579) and entrepreneurship educational outcomes (rc=0.331). It is also found that the passion (rc = 0.31) and innovativeness (rc = 0.2771) are positively correlated with entrepreneurship educational outcome. Moreover, institutional environment has a greater impact on passion (rc = 0.531). Thus, the results indicate that higher education institutions play an important role in promoting passion and innovativeness among students. [ABSTRACT FROM AUTHOR]

• The new fusion of mutual information with OTSU threshold (MI_OTSU) method used for hyperspectral band selection. • The performance of the classification accuracy improved high. • 92.16% of average accuracy achieved with less number on 36 bands. Hyperspectral data are a curse with huge dimensionality, high redundancy of spectral information, and are noisy in nature. Hundreds of narrow adjacent bands are present in HS (Hyperspectral) data with high spectral information and it always leads to a computational complexity in space and time. The information theoretic methods are used for hyperspectral band selection to avoid computational complexity. In order to address this issue, the new fusion of Mutual Information (MI) with Otsu (MI_Otsu) threshold method is proposed for hyperspectral band selection by employing three different entropy measures such as joint, conditional, and relative. The proposed approach identifies the probabilities, entropy, and mutual information between two hyperspectral bands. The optimal threshold is obtained using Otsu multi-threshold technique and highly informative bands will be selected. In addition, the SVM (Support Vector Machine) classification technique is adapted for further classification of selected bands to analyze the performance of the proposed algorithm. The experimental analysis is carried out using the real-time dataset from the test site 'Indian Pines' in Northwestern Indiana recorded by AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) sensor that demonstrates the effectiveness of this proposed approach. It is proved that the proposed work shows the competitive performance even with less selected bands and the relative MI_Otsu method shows a higher accuracy of 92.16% with the comparison of joint and conditional MI_Otsu. [ABSTRACT FROM AUTHOR]

Facial Landmark discovery is an imperative issue in numerous PC vision applications about appearances. It is extremely testing as human faces in wild conditions regularly present expansive varieties fit as a fiddle because of various stances, impediments or demeanors. Profound neural systems have been connected to take in the guide from face pictures to confront shapes. To the best of our insight, Recurrent Neural Network (RNN) has not been utilized in this issue yet. In this paper, we propose a technique which uses RNN and Deep Neural Network (DNN) to take in the face shape. To start with, we design a system utilizing Convolutional Neural Network (CNN) to get the underlying Landmark estimation of appearances. At that point, we utilize feed-forward neural systems for neighborhood look where a segment based seeking technique is investigated. By utilizing LSTMCNN- RNN, the underlying estimation is more dependable which makes the accompanying segment based pursuit doable and exact. Tests demonstrate that the worldwide system utilizing CNN-LSTM-RNN shows signs of improvement results than past systems in the two recordings and single picture. Our technique beats the cutting edge calculations particularly regarding fine estimation of Landmark spots. [ABSTRACT FROM AUTHOR]

Privacy preserving is critical in the field of where data mining is transformed into cooperative task among individuals. In data mining, clustering algorithms are most skilled and frequently used frameworks. In this paper, we propose a privacy-preserving threshold clustering that uses code based technique with threshold estimation for sharing of secret data in privacy-preserving mechanism. The process includes code based methodology which enables the information to be partitioned into numerous shares and handled independently at various servers. The proposed method takes less number of iterations in comparison with existing methods that does not require any trust among the clients or servers. The paper additionally provides experimental results on security and computational efficiency of proposed method. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Infection can present either as articular problems or as complicate on undergoing rheumatological disease. Methods: A retrospective analysis of 1900 inpatients admitted over a 2-year period was done. Infections in these patients were analyzed. Results: Around 0.21% of the patients had septic arthritis, 0.68% had tuberculosis, 0.95% had reactive arthritis, and 0.57% had post-viral arthritis. Bacterial, viral, and fungal infections were common in patients on immunosuppressives, on high disease activity, with diabetes, and with poor renal function. Escherichia coli and Klebsiella pneumoniae were the common infection. [Copyright &y& Elsevier]