Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Information and Communication Technology (ICT) Infrastructure on Economic Growth and Income Inequality in Indonesia

Information and Communication Technology (ICT) plays an important role in supporting economic growth and overcoming income inequality. ICT infrastructure functions to facilitate the use of ICT by economic actors through ICT devices. Previous research used more data between countries or between districts/cities while Indonesia consisted of provinces with different social and economic characteristics. Therefore, the purpose of this study is to analyze the impact of ICT infrastructure on economic growth and income inequality in Indonesia using provincial panel data for the period 2011-2016. The results of the analysis of simultaneous equation models using the Two Stages Least Square (TSLS) method state that ICT infrastructure indicators consisting of cellular telephone ownership, internet accessibility, and the number of Base Transceiver Station (BTS) significantly has a positive impact on economic growth. In addition, these ICT infrastructure variables indirectly have an impact on income inequality through economic growth. Other results obtained are that government spending on ICTs do not significantly impact economic growth and income inequality in Indonesia. The conclusion is that ICT infrastructure has a direct impact on economic growth and an indirect impact on income inequality.
Impact of Information and Communication Technology (ICT) on the Growth of Microfinance Institutions (MFIs) in Zimbabwe

The aim of the study was to evaluate the impact of Information and Communication Technology on the growth of Microfinance Institutions in Zimbabwe. The study used a sample of thirty (30) MFIs registered with the Reserve Bank of Zimbabwe, with operations in Harare Central Business District. A sequential explanatory research design was adopted with the view of adopting a mixed research approach. Purposive sampling technique was adopted. Data was gathered through interviews which were administered to branch managers of MFIs and questionnaires which were administered to MFI employees. The study revealed that most of the MFIs have partially adopted ICT. The study found out that customers’ lack of knowledge in the use of ICT, higher costs of setting up ICT, customers’ lack of ICT resources, poor network connectivity and ICT related complaints raised by MFI clients are the challenges faced by MFIs in adopting and using technology. The study revealed that adoption and usage of ICT has positively affected the operational growth of MFIs through improving revenue base, customers’ touch points, market share, and outreach to previously inaccessible customers, debt recovery and customers’ contact points. The study revealed that adoption and usage of ICT has positively affected the business efficiencies of MFIs through improvement in speed of execution of transactions, loan processing, communication with clients and business acumen of MFI employees. The study recommends that MFIs should advocate the institutions of higher learning in Zimbabwe to introduce banking and finance programmes linked with technology. The study also recommended that there should be collaboration between MFIs, technology companies and higher learning institutions to come up with technology driven products that are accessible and affordable to MFI clients.
Impact of Information and Communication Technology (ICT) on Students' Academic Performance of Kaduna State University, Kaduna State, Nigeria

his study accessed the relationship between ICT T tools and academic performance of undergraduate students in Kaduna State University, Kaduna adopting a descriptive survey research design and anchored on the 'constructivist theory'. The population of the study comprised of all undergraduate students in Kaduna State University (Main Campus), Tafawa Balewa Way, Kaduna, while a sample of 350 students was selected using proportionate stratified random sampling technique. The study utilized primary data which were collected using a questionnaire, while data analysis was performed using descriptive statistics (frequency, percentage, mean, and standard deviation) and OLS – multiple regression analysis. Findings from the study revealed that ICT tools have significant positive relationship with the academic performance of undergraduate students in Kaduna State University at 5% level of significance. Findings also revealed that the ICT tools - Internet, Laptop/Desktop, Printer, Browser Phone, and Digital Camera have individual significant positive impacts on the academic performance of undergraduate students in Kaduna State University at 5% level of significance. Hence, the study concludes that ICT tools have significant positive relationship with the academic performance of undergraduate students in Kaduna State University, and the ICT tools - Internet, Laptop/Desktop, Printer, Browser Phone, and Digital Camera have individual significant positive impacts on the academic performance of the students. The study therefore, recommended that management of Kaduna State University should endeavour to provide proper orientation for undergraduate students on how to use, when to use, and purpose for using diverse ICT tools in their academic pursuits in order to achieve and sustain positive academic gains from their utilization, among other recommendations
Uniform Hazard Ground Motions and Response Spectra for Mid-America Cities

Introduction Mid-America is a region of moderate seismicity. Infrequent moderate to large events had occurred in the past and can occur again and cause large losses. The performance of the building stock and other structures under future earthquakes is a serious concern. The major threats of future seismic events come from the New Madrid Seismic Zone (NMSZ) and several other areas of moderate seismicity. As ground motion records of engineering interest in this area have been scarce, to evaluate the performance of buildings and structures and estimate loss/cost, simulation of future events based on current data and knowledge is necessary. A method of simulation is developed for this purpose. The method is based on the latest information of seismicity in this region, the most recent ground motion models and simulation methods appropriate for engineering applications in this region. A strong emphasis is placed on uncertainty modeling and efficiency in application to performance evaluation and fragility analysis. The procedure may be improved as more knowledge on earthquakes in this region and more accurate and efficient methods of ground motion modeling become available. A brief description of the method of simulation and results obtained for three Mid-America cities is given in the following. These cities are selected for study because they present a cross-section of the mid-America cities at risk. Since ground motions are strongly dependent on local soil condition and yet the soil profile variation within a city has not been mapped in detail, in this study the soil condition of a city will be assumed to have small variation and can be approximately modeled by a generic profile. Ground motions at the bedrock, however, will also be generated for these cities that if detailed information of local soil variation is available, one can use appropriate soil amplification computer software to obtain the surface ground motions. The ground motion simulation method basically follows the procedure proposed by Herrmann and Akinci (1999) that is largely based on Boore's point-source simulation method SMSIM (1996). To catch some of the important near-source effects due to large events, however, the finite fault model by Beresnev and Atkinson (1997, 1998) is also used for magnitude-8 events. The soil amplification is modeled by the quarter-wavelength method by Boore and Joyner (1991, 1997). The tectonic and seismological data are mainly taken from USGS Open-File Report 96-532 (Frankel et al. 1996). A large number of possible future events and …
Layer-Specific Characteristics of Artificial Representations in the Trained AlexNet Model

Analysis of trained deep convolutional neural networks (DCNNs) provides insight into the mechanism of biological visual systems for visually recognizing objects. However, the detailed characteristics of artificial representations for object classification remain unclear at the layer level of DCNNs. Previous studies have found that stylized images generated from natural images by changing their textures may underlie the object classification performed by trained DCNN models (such as the AlexNet model) and modulate the artificial representations of their model neurons in hidden layers. In this study, we analyzed the characteristics of the artificial representations in each layer of a trained AlexNet model by computing the correlation between natural and stylized images according to the activities of model neurons. The activities of model neurons in response to these natural and stylized images were highly correlated in the low-level layers of the trained AlexNet model. However, the magnitude of the correlation decreased as the level of the model layer increased. These results imply that a trained AlexNet model may establish texture-based representations of images through the hierarchy of its network. This finding is in agreement with results of previous studies, and implies that artificial representations for object classification performed by DCNN models correspond, at least in part, to neural representations for visual perception of objects.
Phytochemical Screening and Antioxidant Activities of Geniotrigona thoracica Propolis Extracts Derived from Different Locations in Malaysia

Propolis, a natural resinous substance secreted by bees, has garnered considerable interest due to its diverse bioactive compounds and potential health benefits. Nevertheless, the phytochemical composition of propolis exhibits significant variation, influenced by multiple factors including geographical region, and botanical origin. These determinants exert profound effects on the distinctive properties and biological diversities of propolis. This study aimed to investigate the phytochemical composition and antioxidant activities of Geniotrigona thoracica propolis extracts collected from three apiary sites, designated as apiary A, apiary B, and apiary C, located in different regions within Selangor. The ethanolic extracts of propolis were prepared using 70% of ethanol and subjected to phytochemical screening to identify the presence of flavonoids, terpenoids, alkaloids, saponins, tannins, steroids, and cardiac glycosides, whilst the total phenolic content (TPC) and total flavonoid content (TFC) were measured using the Folin-Ciocalteu colorimetric and aluminium chloride methods, respectively. Additionally, the antioxidant activities of the propolis extracts were evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and ferric-reducing antioxidant power (FRAP) assays. The phytochemical screening revealed the presence of flavonoids, terpenoids, alkaloids, saponins, tannins, steroids, and cardiac glycosides in all propolis extracts. The propolis from apiary A exhibited significantly higher TPC (302.21 ± 0.11 mg/mL GAE) and TFC values (99.08 ± 0.03 mg/mL QE) compared to apiary B and C. The results also indicated that propolis from apiary A possessed significantly higher antioxidant activities, with IC₅₀ value of DPPH at 25.27 μg/mL and FRAP value of 727.53 ± 0.09 μM Fe²+, in comparison to apiary B and C. A strong correlation was observed between TPC, TFC, and IC₅₀ of DPPH. This study highlights significant variations in the phytochemical compositions and antioxidant activities of propolis samples collected from different geographical and botanical sources. Further investigation is in progress to identify the specific phytochemical constituents responsible for these variations.
Prevalence of Sleep Disturbances in Latin American Populations and Its Association with Their Socioeconomic Status—A Systematic Review and a Meta-Analysis

Background: The worldwide increase in the prevalence and incidence of sleep disturbances represents a major public health issue. Among multiple determinants affecting sleep health, an individual’s socioeconomic status (SES) is the most ignored and underestimated throughout the literature. No systematic review on the relation between SES and sleep health has been previously conducted in Latin America. Methods: PRISMA guidelines were used. Results: Twenty articles were included in the final sample (all cross-sectional studies), and twelve among them were rated as fair or poor quality. Among these studies, 80.0% (n = 16) were performed in Brazil, 10.0% (n = 2) were performed in Peru, 5.0% (n = 1) were performed in Chile, and 5.0% (n = 1) were multicentric (11 countries). The combined total number of participants was N = 128.455, comprising 3.7% (n = 4693) children, 16.0% (n = 20,586) adolescents, and 80.3% (n = 103,176) adults. The results show the following: (1) The sleep outcomes analyzed were sleep duration, sleep quality/sleep disturbance, insomnia, excessive daytime sleepiness (EDS), obstructive sleep apnea (OSA)/sleep-disordered breathing (SDB) symptoms, and bruxism. (2) The most used determinants were income, education level, employment status/occupation, wealth/assets, and composite indices. (3) Higher SES was associated with shorter sleep duration. (4) Lower SES was associated with a decrease in sleep quality, less frequent snoring, more prevalent EDS, and sleep bruxism. (5) Lower education was associated with insomnia. (6) Higher education was associated with more sleep bruxism. (7) The pooled prevalence using a meta-analysis of the random effects model was 24.73% (95%CI, 19.98–30.19), with high heterogeneity (I2 = 100%). (8) The prevalence of sleep disturbances decreased with high education (OR, 0.83; 95%CI, [0.69–0.99]; I2 = 79%), while it increased with low income (OR, 1.26; 95%CI, [1.12–1.42]; I2 = 59%), unemployment (OR, 2.84; 95%CI, [2.14–3.76]; I2 = 0%), and being a housewife (OR, 1.72; 95%CI, [1.19–2.48]; I2 = 55%). Discussion: This meta-analysis shows that lower SES (education, income, and work) was associated with sleep disturbances in Latin America. Therefore, sleep disturbance management should be addressed with a multidimensional approach, and a significant investment in targeted public health programs to reduce sleep disparities and support research should be made by the government before the situation becomes uncontrollable.
Chinese Medical Named Entity Recognition Based on Fusion of Global Features and Multi-Local Features

Chinese medical Named Entity Recognition (NER) is a task of Natural Language Processing (NLP), which aims to extract key information from Chinese medical texts. Recently, Transformer becomes the mainstream approach for NLP due to its powerful capability for global feature extraction. However, entities usually appear in the form of subsequences in NER, therefore the local features are not negligible, and the uncertainty of Chinese word segmentation increases the difficulty of this task. In this paper, we propose a network structure that combines global feature extraction and multi-local feature extraction to enhance the performance of Chinese medical NER. Based on the global feature extracted by the Transformer, Bi-LSTM is used to extract the multi-local features, and a context integration mechanism is used to enhance local features by integrating both forward and backward global contexts in each cell. This allows for a more comprehensive representation of individual cells. And a feature fusion method based on attention mechanism is proposed, which allows the decoder to better focus on the more important information for predicting the current character. During the global feature extraction, the flat-lattice structure is introduced to generate all the potential results of Chinese word segmentation. And the span-based relative positional encoding integrates direction and distance perception, which overcomes the shortcoming of Transformer’s inability to capture sequential characteristics. Finally, a CRF with conditional constraints is used as the decoder of the model. Experimental results on two benchmark datasets show the effectiveness of our model, and the method significantly outperforms the state-of-the-art methods in the medical NER task, achieving $F1$ value of 93.64% on CCKS2017 and 85.01% on CCKS2019.
Perioperative Pain Management and Cancer Outcomes: A Narrative Review

Abstract Cancer-related pain is one of the most common and incapacitating symptoms for cancer patients. Cancer pain can be caused by diagnostic or therapeutic procedures, side effects and toxicity from therapy, or the cancer itself. Uncontrolled cancer-related pain is associated with inadequate quality of life and reduced functional status. Optimal pain management during the perioperative period requires a tailored approach. Interventions that are recommended for the management of acute surgical pain include regional anesthesia, local anesthetic infusions, non-opioid analgesics (ketamine, dexmedetomidine, lidocaine, and non-steroidal anti-inflammatory drugs), and opioids. Despite continued research efforts and advances in cancer treatment, opioids remain the most effective medication to treat moderate to severe cancer-related pain; however, their role has been changing significantly due to the opioid epidemic and opioid misuse. While pre-clinical and retrospective studies have shown a negative association between opioid use and cancer outcomes, randomized control trials have failed to confirm this association. The purpose of this review is to summarize the pharmacological management of acute cancer-related pain during the perioperative period with an emphasis on cancer recurrence.
Primary Care: Can It Solve Employers' Health Care

Employers are beginning to recognize that investing in the primary care foun- dation of the health care system may help address their problems of rising health care costs and uneven quality. Primary care faces a crisis as a growing number of U.S. medical graduates are avoiding primary care careers because of relatively low reimbursement and an unsatisfying work life. Yet a strong primary care sector has been associated with re- duced health care costs and improved quality. Through the Patient-Centered Primary Care Collaborative and other efforts, some large employers are engaged in initiatives to strengthen primary care. (Health Affairs 27, no. 1 (2008): 151-158; 10.1377/hlthaff.27. 1 . 151)
Outer vortex wind structure changes during and following tropical cyclone secondary eyewall formation in the Atlantic

ABSTRACT Some recent studies have utilized flight-level (700 mb) winds to document the maximum wind speeds (Vmax) and radius of Vmax (Rmax) of the original and secondary eyewalls during 24 Atlantic hurricane eyewall replacement cycles (ERC). In this study, Hurricane Wind (H*Wind) analyses of Atlantic hurricanes during 2003-2005 are utilized to document changes in the outer vortex surface wind profile beyond the secondary eyewall, with a focus on the radii of gale-force winds (R34) that are often defined operationally as size changes. In Mode 1, complete and partial ERCs in which the pre-, during-, and post-ERC outer wind profiles have approximately the same shape, the outward displacements of Rmax leads to size (R34) increases as much as 100 km. Mode 2 ERCs are characterized by sharpened wind profiles outside the secondary eyewall that offset the larger Rmax radii to produce only small R34 increases. While statistically significant results are not obtained, the differences in size changes for Mode 1 and Mode 2 SEF cases suggest practical significance for forecasts and warnings.
Examining impulsivity as an endophenotype using a behavioral approach : a DRD 2 TaqI A and DRD 4 48-bp VNTR association study

Background: Research on the genetic basis for impulsivity has revealed an array of ambiguous findings. This may be a result of limitations to self-report assessments of impulsivity. Behavioral measures that assess more narrowly defined aspects of impulsivity may clarify genetic influences. This study examined the relationship between possession of the DRD2 TaqI A and DRD4 48 bp VNTR genetic polymorphisms and performance on a behavioral measure of impulsivity, the delay discounting task (DDT), and three traditional self-report measures. Methods: 195 individuals (42% male) were recruited from a university campus and were assessed in small group sessions using personal computers. Genotyping was conducted using previously established protocols. For the DRD2 TaqI A locus, individuals were designated as possessing at least one copy of the A1 allele (A1+) or not (A1-), and for the DRD4 48-bp VNTR locus, individuals were designated as having at least one long allele (7 repeats or longer, L+) or not (L-). Principal analyses used multiple univariate factorial 2 (A1+/A1-) × 2 (L+/L-) analyses of variance. Results: A significant main effect of A1+ status on DDT performance was evident (p = .006) as well as a significant interaction effect (p = .006) between both genes. No other significant effects were evident on the self-report measures, with the exception of a trend toward an interaction effect on the Sensation Seeking Scale. Exploratory analyses suggested that the significant effects were not a function of population stratification or gender. Discussion: These data suggest that the DRD2 TaqI A and DRD4 VNTR polymorphisms influence impulsivity as measured with a delay discounting task. Specifically, these findings suggest that an interaction between the functional effects of the two unlinked genotypes results in significant difference in the balance of mesolimbic dopaminergic activation relative to frontal-parietal activation. However, these findings are also the first in this area and must be replicated. Conclusion: These findings suggest a meaningful interaction between the DRD2 TaqI A and DRD4 VNTR polymorphisms in the expression of impulsivity and provide initial support for the utility of using behavioral measures for clarifying genetic influences on impulsivity. Published: 10 January 2007 Behavioral and Brain Functions 2007, 3:2 doi:10.1186/1744-9081-3-2 Received: 2 October 2006 Accepted: 10 January 2007 This article is available from: http://www.behavioralandbrainfunctions. com/content/3/1/2 © 2007 Eisenberg et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.