Assessment of Information Literacy Abilities: A Case Study of Pakistan

This study aimed to assess undergraduate students’ Information Literacy (IL) abilities in Pakistan. A survey method was employed to collect the necessary data from the population. The participants consisted of students from the Capital University of Science and Technology (CUST), COMSATS University Islamabad, Bahria University (BU) Islamabad, and the Federal Urdu University of Arts, Sciences and Technology (FUUAST). The sample consisted of 200 students, randomly selected. A questionnaire was formulated and completed individually. The results produced an alarming result for the selected institutions, as about 52% of students reported that they never went to the library. A similar situation was found across the selected universities, though with BU surpassing other universities with respect to daily use of the library. The responses to the survey indicated students were in a poor position in terms of their ability to identify information sources. Furthermore, most item scores were less than two, indicating that students’ recognition and understanding of information sources was in a dangerously precarious condition. The findings also indicated that students’ ability to access and use information for assignments, tests, examinations, and the writing of research articles was extremely limited. This could have severe implications for their learning outcomes. According to our findings, students’ ability to implement technical best practice in academic work and research was extremely limited, as was their knowledge of and practice in providing appropriate credit to original authors. On the other hand, the students’ ability to use social media applications, such as Facebook, Instagram, and LinkedIn, was relatively strong. We recommend that university libraries should be more involved in the educational process. This study should contribute considerably to the organization of different IL programs in universities to promote, develop, and improve students’ IL abilities

Scrutinizing the Adoption of Integrated Project Delivery in the Kingdom of Saudi Arabia Construction Sector

The Integrated Project Delivery (IPD) approach has been acquiring applause worldwide attributable to its certified and attested outcomes in efficiently sharing threats and costs confronting the construction project. Regardless of its popularity and rationality, no substantial studies have been conducted into the Kingdom of Saudi Arabia’s (KSA) construction. Hence, the novelty of this paper is probing the Saudi Arabia government tender process and procurement regulation for IPD theme deployment, reliant on a thorough literature assessment to bestow construction parties with the barriers of incorporating the IPD paradigm in KSA. The research objectives are attained via a questionnaire survey steered toward (1) pondering respondents’ cognizance of IPD eventuality and deployment in the KSA’s construction sector, (2) stipulating the survey’s participants’ preparedness for IPD implementation in KSA’s construction market, (3) specifying the project phase in which the contractor should be entangled as part of the IPD method, and (4) scrutinizing the respondents’ knowledge to classify the anticipated barriers to IPD from the global market in KSA. Findings unearth that the KSA construction sector still entails being more conscientious and adequate, pointing out the difficulties triggered by a dearth of awareness, apprehension, and pragmatic implementation. Further, respondents showed impartiality towards construction project stakeholders’ prescience and exuberance, the existing government procurement and tendering laws, and revolutionary technological infrastructure and competency for IPD implementations in the KSA construction industry. Additionally, the contractor should be implicated and embroiled in the construction project from the early design phase. Addedly, the hurdles to deploying IPD in KSA are ranked as follows: technological, knowledge, financial, legal, and cultural barriers

Cupping Therapy Simulation Course; A Pilot Study Assessing Self Reporting of Confidence, Expectations/Satisfaction and Performance

This paper aimed to assess self-reporting of confidence, expectations/satisfaction, and performance of medical students before and after the cupping therapy simulation training course and to validate cupping simulation training evaluation questionnaire (CSTEQ). It was a pilot study to evaluate cupping therapy simulation course provided by National Center for Complementary and Alternative Medicine (NCCAM).  The number of participants was 29/41 (70.7%) (20 females and 9 males) before training and 20/41 (48.9%) (9 females and 11 males) after training who returned the (CSTEQ) questionnaire. A significant improvement of performance scale and total score were noted after the cupping simulation training. Significant differences in confidence (P=0.013), expectations/satisfaction (P=0.001), performance (P=0.007) and total scoring (P=0.001) between male and female medical students were noted in favor of males. We can conclude that medical students reported significant improvement in performance and overall scoring after cupping therapy simulation course. Cupping simulation training evaluation questionnaire (CSTEQ) may be a reliable test tool. Cupping therapy simulation course should be encouraged, updated and extended to satisfy the learning needs especially of the female medical student. Future large-scale studies were recommended

An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine

Multispectral palmprint recognition system (MPRS) is an essential technology for effective human identification and verification tasks. To improve the accuracy and performance of MPRS, a novel approach based on autoencoder (AE) and regularized extreme learning machine (RELM) is proposed in this paper. The proposed approach is intended to make the recognition faster by reducing the number of palmprint features without degrading the accuracy of classifier. To achieve this objective, first, the region of interest (ROI) from palmprint images is extracted by David Zhang’s method. Second, an efficient normalized Gist (NGist) descriptor is used for palmprint feature extraction. Then, the dimensionality of extracted features is reduced using optimized AE. Finally, the reduced features are fed to the RELM for classification. A comprehensive set of experiments are conducted on the benchmark MS-PolyU dataset. The results were significantly high compared to the state-of-the-art approaches, and the robustness and efficiency of the proposed approach are revealed

Recommending Reforming Trip to a Group of Users

With the quick evolution of mobile apps and trip guidance technologies, a trip recommender that recommends sequential points of interest (POIs) to travelers has emerged and recently received popularity. Compared to other outing recommenders, which suggest the following single POI, our proposed trip proposal research centers around the POI sequence proposal. An advanced sequence of the POI recommendation system named Recommending Reforming Trip (RRT) is presented, recommending a dynamic sequence of POIs to a group of users. It displays the information progression in a verifiable direction, and the output produced is the arrangement of POIs to be expected for a group of users. A successful plan is executed depending upon the deep neural network (DNN) to take care of this sequence-to-sequence problem. From start to finish of the work process, RRT can permit the input to change over time by smoothly recommending a dynamic sequence of POIs. Moreover, two advanced new estimations, adjusted precision (AP) and sequence-mindful precision (SMP), are introduced to analyze the recommended precision of a sequence of POIs. It considers the POIs’ consistency and also meets the sequence of order. We evaluate our algorithm using users’ travel histories extracted from a Weeplaces dataset. We argue that our algorithm outperforms various benchmarks by satisfying user interests in the trips

Recommending Reforming Trip to a Group of Users

With the quick evolution of mobile apps and trip guidance technologies, a trip recommender that recommends sequential points of interest (POIs) to travelers has emerged and recently received popularity. Compared to other outing recommenders, which suggest the following single POI, our proposed trip proposal research centers around the POI sequence proposal. An advanced sequence of the POI recommendation system named Recommending Reforming Trip (RRT) is presented, recommending a dynamic sequence of POIs to a group of users. It displays the information progression in a verifiable direction, and the output produced is the arrangement of POIs to be expected for a group of users. A successful plan is executed depending upon the deep neural network (DNN) to take care of this sequence-to-sequence problem. From start to finish of the work process, RRT can permit the input to change over time by smoothly recommending a dynamic sequence of POIs. Moreover, two advanced new estimations, adjusted precision (AP) and sequence-mindful precision (SMP), are introduced to analyze the recommended precision of a sequence of POIs. It considers the POIs’ consistency and also meets the sequence of order. We evaluate our algorithm using users’ travel histories extracted from a Weeplaces dataset. We argue that our algorithm outperforms various benchmarks by satisfying user interests in the trips

Ex Vivo Antiplatelet and Thrombolytic Activity of Bioactive Fractions from the New-Fangled Stem Buds of <i>Ficus religiosa</i> L. with Simultaneous GC-MS Examination

Different parts of Ficus religiosa are the common components of various traditional formulations for the treatment of several blood disorders. The new-fangled stem buds’ powder was extracted with 80% ethanol and successively fractionated by chloroform and methanol. Chloroform and methanol fractions of Ficus religiosa (CFFR and MFFR) were tested for antiplatelet, antithrombotic, thrombolytic, and antioxidant activity in ex vivo mode. The MFFR was particularly investigated for GC-MS and toxicity. The antiplatelet activity of the CFFR, MFFR, and standard drug aspirin at 50 μg/mL was 54.32%, 86.61%, and 87.57%, and a significant delay in clot formation was noted. CFFR at different concentrations did not show a significant effect on the delay of clot formation, antiplatelet, and free radical scavenging activity. The most possible marker compounds for antiplatelet and antioxidant activity identified by GC-MS in the MFFR are salicylate derivatives aromatic compounds such as benzeneacetaldehyde (7), phenylmalonic acid (13), and Salicylic acid (14), as well as Benzamides derivatives such as carbobenzyloxy-dl-norvaline (17), 3-acetoxy-2(1H)-pyridone (16), and 3-benzylhexahydropyrrolo [1,2-a] pyrazine-1,4-dione (35). A toxicity study of MFFR did not show any physical indications of toxicity and mortality up to 1500 mg/kg body weight and nontoxic up to 1000 mg/kg, which is promising for the treatment of atherothrombotic diseases

Analysis of Climate Change Impacts on the Food System Security of Saudi Arabia

Climate change poses a challenge to the security and long-term viability of the global food supply chain. Climate unpredictability and extreme weather events have significant impacts on Saudi Arabia’s vulnerable food system, which is already under stress. The Kingdom of Saudi Arabia faces distinct challenges in comparison to other dry locations across the world. Here, the per capita water demand is high, the population is growing, the water resources are extremely limited, and there is little information on the existing groundwater supplies. Consequently, it is anticipated that there will be formidable obstacles in the future. In order to make data-driven decisions, policymakers should be aware of causal links. The complex concerns pertaining to the Saudi Arabian food system were analyzed and rationally explained in the current study. A causality analysis examined different driving factors, including temperature, greenhouse gas (GHG) emission, population, and gross domestic product (GDP) that cause vulnerabilities in the country’s food system. The results of the long-run causality test show that GDP has a positive causal relationship with the demand for food, which implies that the demand for food will increase in the long run with an increase in GDP. The result also shows that Saudi Arabia’s GDP and population growth are contributing to the increase in their total GHG emissions. Although the Kingdom has made some efforts to combat climate change, there are still plenty of opportunities for it to implement some of the greatest strategies to guarantee the nation’s food security. This study also highlights the development of appropriate policy approaches to diversify its import sources to ensure future food security