Background and objective The anti-inflammatory properties of vitamin C (VC) and the promising results it has shown in the treatment for common cold have prompted clinicians to use it as adjuvant therapy in the treatment of COVID-19. The purpose of this study was to find out the role of VC as adjunctive therapy in coronavirus disease 2019 (COVID-19). Methodology This study was conducted from March to July 2020 in the COVID-19 unit of a tertiary care hospital in Karachi. In this randomized controlled trial (RCT), one group received the intervention [50 mg/kg/day of intravenous (IV) VC] along with the standard therapy, and the other group received standard therapy only. Data such as age, gender, vitals, and biochemical values as well as outcomes including the number of days required for treatment, hospital stay, need for ventilation, and mortality were compared between the two groups and recorded using a self-structured questionnaire. Results COVID-19 patients who received IV VC became symptom-free earlier (7.1 ± 1.8 vs. 9.6 ± 2.1 days, p-value: <0.0001) and spent fewer days in the hospital (8.1 ± 1.8 vs. 10.7 ± 2.2 days, p-value: <0.0001) compared to those who received standard therapy only. However, there was no significant difference in the need for mechanical ventilation (p-value: 0.406) and mortality (p-value: 0.31) between the two groups. Conclusion VC can significantly improve clinical symptoms in patients affected with COVID-19; however, it had no impact on mortality and the need for mechanical ventilation. More large-scale studies are required to further assess the role of VC in the treatment of COVID-19.

Traditionally, firms tend to incline toward financial performance and profitability to surge shareholder's wealth. In the modern day, in addition to financial performance, innovative and environmental performance has also become a central effort. However, all firms are not flourished in the achievement of financial, innovative, and environmental performance, particularly small‐ and medium‐sized enterprises (SMEs), which need adequate financial resources due to lack of resources and can search for opportunities to boost their performance. This research examines the role of financial availability in financial, innovative, and environmental performance with a mediating role of opportunity recognition. Empirical evidence is collected through structured questionnaires from 347 SMEs operating in the emerging market Pakistan. Hypotheses are tested in Analysis of a Moment Structure (AMOS) using structural equation modeling. Results indicate that satisfactory financial resources significantly contribute to financial and innovative performance but play an insignificant role in environmental performance as well. In addition, firms with enough financial capital recognize new opportunities significantly via opportunity recognition mediator, where partially mediating the relation between financial availability and financial/innovative performance. However, firms fully mediate the link between financial availability and environmental performance. Our research findings recommend CEOs and top managers to utilize their financial resources in an efficient way to achieve the advantage of the new opportunity recognition, superior financial, innovative, and environmental performance.

A mobile ad-hoc network (MANET) is a temporary network of wireless mobile nodes. In a MANET, it is assumed that all of the nodes cooperate with each other to transfer data packets in a multi-hop fashion. However, some malicious nodes don’t cooperate with other nodes and disturb the network through false routing information. In this paper, we propose a prominent technique, called dual attack detection for black and gray hole attacks (DDBG), for MANETs. The proposed DDBG technique selects the intrusion detection system (IDS) node using the connected dominating set (CDS) technique with two additional features; the energy and its nonexistence in the blacklist are also checked before putting the nodes into the IDS set. The CDS is an effective, distinguished, and localized approach for detecting nearly-connected dominating sets of nodes in a small range in mobile ad hoc networks. The selected IDS nodes broadcast a kind of status packet within a size of the dominating set for retrieving the complete behavioral information from their nodes. Later, IDS nodes use our DDBG technique to analyze the collected behavioral information to detect the malicious nodes and add them to the blacklist if the behavior of the node is suspicious. Our experimental results show that the quality of the service parameters of the proposed technique outperforms the existing routing schemes.

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BackgroundAggression and Violence against primary care physicians is reportedly common in Pakistan but there is no any documented study to-date on this burning issue.MethodsA formed written questionnaire was distributed among 769 primary care physicians aged 31 ± 7.68 years. Apart from the demographic data, the questionnaire included questions regarding the level of safety that primary care physicians felt during their work setups and on-call duties, along with the experience of aggression against them by the perpetrators & the support provided by the hospital management in such cases.ResultResponse rate was 68% i.e. 524 physicians agreed to participate in the study. It was found that majority (85%) of the physicians has faced mild events, 62% have faced moderate events and roughly 38% were subjected to severe violence. Some physicians revealed more than one form of aggression being faced by them in 12 months preceding months which makes the collective percentage greater than 100%. Verbal abuse is the most frequent type of mistreatment faced by the doctors from the patients or their attendants.ConclusionA considerable number of physicians participated have faced mild violence in which verbal abuse was commonest; followed by moderate and severe events.

Short-term traffic state prediction has become an integral component of an advanced traveler information system (ATIS) in intelligent transportation systems (ITS). Accurate modeling and short-term traffic prediction are quite challenging due to its intricate characteristics, stochastic, and dynamic traffic processes. Existing works in this area follow different modeling approaches that are focused to fit speed, density, or the volume data. However, the accuracy of such modeling approaches has been frequently questioned, thereby traffic state prediction over the short-term from such methods inflicts an overfitting issue. We address this issue to accurately model short-term future traffic state prediction using state-of-the-art models via hyperparameter optimization. To do so, we focused on different machine learning classifiers such as local deep support vector machine (LD-SVM), decision jungles, multi-layers perceptron (MLP), and CN2 rule induction. Moreover, traffic states are evaluated using traffic attributes such as level of service (LOS) horizons and simple if–then rules at different time intervals. Our findings show that hyperparameter optimization via random sweep yielded superior results. The overall prediction performances obtained an average improvement by over 95%, such that the decision jungle and LD-SVM achieved an accuracy of 0.982 and 0.975, respectively. The experimental results show the robustness and superior performances of decision jungles (DJ) over other methods.

Due to the dynamism of topology, sharing of bandwidth and constraint of resources in wireless nodes, the provision of quality of service (QoS) for routing in mobile ad hoc networks (MANETs) presents a great challenge. Security is another crucial aspect of providing QoS since the existence of malicious nodes present all kinds of threats to MANETs. Although a number of mechanisms have been proposed for protecting MANETs, most of the solutions are only effective for a particular kind of attacks or provide security at the cost of sacrificing QoS. In this paper, we propose a trust-based secure QoS routing scheme by combining social and QoS trust. The primary approach of the proposed scheme relies on mitigating nodes that exhibit various packet forwarding misbehavior and on discovering the path that ensures reliable communication through the trust mechanism. The scheme would select the best forwarding node based on packet forwarding behavior as well as capability in terms of QoS parameters, such as residual energy, channel quality, link quality, etc. We will present an adversary model for packet dropping attack against which we evaluate the proposed scheme. Simulation experiment using Network Simulator-2 (NS2) and under various network conditions show that mixing social and QoS trust parameters can greatly improve security and quality of service routing in terms of overhead, packet delivery ratio and energy consumption.

Introduction: Angiotensin-converting enzyme inhibitor (ACEI) and angiotensin II receptor blockers (ARBs) are taken as the first treatment option for hypertensive patients. The various global trials have suggested that ACEIs and ARBs may increase risk of lung cancer; however, the results are contradictory and there is no local study available. This study is conducted to compare the incidence of lung cancers in patients on ACEIs and ARBs.Methods: This retrospective study, conducted in a major cardiology unit of a tertiary care hospital in Pakistan, included patients diagnosed with hypertension, between 2005 and 2010, who were prescribed either ACEIs or ARBs. During the period of 2005 to 2010, 47,823 naïve hypertensive patients were reported in the outpatient department of the cardiology unit. Of which, 22,241 were prescribed ACEI and 25,582 were prescribed ARBs. After sorting patient data based on our inclusion criteria, n = 14,891 participants were included in the ACEI group and n = 19,112 participants were included in the ARB group.Results: The incidence of lung cancer in the ACEI and ARB group was n = 165 and n = 160, respectively. In this study, the overall incidence rates of lung cancer in the ACEI and ARB cohorts were 12.2 and 16.6 per 10,000 person-years, respectively. The hazard ratio was 1.32 (95% confidence interval: 1.06-1.64; p-value: 0.01). Conclusion:In this study, the incidence of lung cancer was relatively more among people using ACEIs than ARBs. Hence, patients undergoing long-term treatment with ACEIs need regular follow-up and proper scanning to avoid grave complications.