Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Esteem and Tendency of Nomophobia in College Students

Nomophobia is defined as the fear of not having anything to do with cell phones. Research shows various psychological factors are involved when someone uses a cell phone excessively, such as low self-esteem. This phenomenon seems to be increasing globally. Addictive behavior related to smartphone use can be considered as part of the broader Nomophobia construct. Excessive use of smartphones is also seen by students who are in the Z generation group and are said to be digital natives. In general, students who are in the age range of 18-22 have quite an extreme dependence on smartphones and digital information using the internet. Examining this phenomenon, this study aims to determine the relationship between self-esteem and the tendency of Nomophobia in college students. This research was conducted on students in East Bekasi with a total sample of 100 male and female students. The research method uses a quantitative approach with a correlational method. The results of the correlation test between self-esteem and Nomophobia tendencies in students in East Bekasi showed a Pearson Product Moment correlation coefficient of 0.069 with a two-tailed test at a confidence level of 0.05 (5%). This means that there is no significant relationship between self-esteem and the tendency of Nomophobia among students.
Potential Oral Microbial Markers for Differential Diagnosis of Crohn’s Disease and Ulcerative Colitis Using Machine Learning Models

Although gut microbiome dysbiosis has been associated with inflammatory bowel disease (IBD), the relationship between the oral microbiota and IBD remains poorly understood. This study aimed to identify unique microbiome patterns in saliva from IBD patients and explore potential oral microbial markers for differentiating Crohn’s disease (CD) and ulcerative colitis (UC). A prospective cohort study recruited IBD patients (UC: n = 175, CD: n = 127) and healthy controls (HC: n = 100) to analyze their oral microbiota using 16S rRNA gene sequencing. Machine learning models (sparse partial least squares discriminant analysis (sPLS-DA)) were trained with the sequencing data to classify CD and UC. Taxonomic classification resulted in 4041 phylotypes using Kraken2 and the SILVA reference database. After quality filtering, 398 samples (UC: n = 175, CD: n = 124, HC: n = 99) and 2711 phylotypes were included. Alpha diversity analysis revealed significantly reduced richness in the microbiome of IBD patients compared to healthy controls. The sPLS-DA model achieved high accuracy (mean accuracy: 0.908, and AUC: 0.966) in distinguishing IBD vs. HC, as well as good accuracy (0.846) and AUC (0.923) in differentiating CD vs. UC. These findings highlight distinct oral microbiome patterns in IBD and provide insights into potential diagnostic markers.
Cross-Kingdom Interaction of miRNAs and Gut Microbiota with Non-Invasive Diagnostic and Therapeutic Implications in Colorectal Cancer

Colorectal cancer (CRC) has one of the highest incidences among all types of malignant diseases, affecting millions of people worldwide. It shows slow progression, making it preventable. However, this is not the case due to shortcomings in its diagnostic and management procedure and a lack of effective non-invasive biomarkers for screening. Here, we discuss CRC-associated microRNAs (miRNAs) and gut microbial species with potential as CRC diagnostic and therapy biomarkers. We provide rich evidence of cross-kingdom miRNA-mediated interactions between the host and gut microbiome. miRNAs have emerged with the ability to shape the composition and dynamics of gut microbiota. Intestinal microbes can uptake miRNAs, which in turn influence microbial growth and provide the ability to regulate the abundance of various microbial species. In the context of CRC, targeting miRNAs could aid in manipulating the balance of the microbiota. Our findings suggest the need for correlation analysis between the composition of the gut microbiome and the miRNA expression profile.
Islamic Perception of Shopping Mall Through the Dimension of Facility Management

A shopping mall refers to a structure with several retail establishments managed as a single property that offers various products and services. It has become essential to the functioning of contemporary society, particularly for residents of urban and suburban areas. However, concerns or issues regarding facilities and services in shopping malls continue to surface even today. Past studies have suggested that facility management is a best practice for overcoming management and operation issues. It also aligns with the Islamic principle as it is beneficial knowledge relevant to the modern management approach. Therefore, this paper seeks to comprehend the potential facility management approach to shopping mall management. The main objective of this study is to emphasize the importance of facility management in shopping malls by evaluating consumer satisfaction. A survey is conducted with a total sample of 200 respondents based on three facility management maintenance characteristics: functional, technical, and image. One of the reputable shopping malls in Johor Bahru is selected for this study because it attracts numerous visitors from throughout Johor Bahru. The results show that most of the visitors are pleased and satisfied with all three aspects from the dimension of facility management.
Angiotensin II Type 1 Receptor Antibody-Mediated Kidney Rejection Unresponsive to Treatment

Allograft rejection is a significant cause of renal transplant failure which needs prompt diagnosis and treatment for graft salvage. Angiotensin II type 1 receptor antibody-mediated rejection (AT1R-AMR) is increasingly being identified as the etiology of antibody-mediated rejection in kidney transplant recipients with allograft rejection but without detectable human leukocyte antigen (HLA) antibodies. While some reports have suggested that AT1R-AMR may be refractory to standard therapy, others have reported improvement or stabilization of graft function. We present two patients in which anti-rejection therapy including therapeutic plasma exchange was unable to salvage the allograft.
RSSI based Device-free Human Identification

Researchers have explored many methods and techniques for human detection and identification in diverse contexts. One such approach is studying variations of Radio Frequency (RF) signals (e.g., Received Signal Strength Indicator (RSSI)). RSSI based techniques have been widely used in human detection, but not for unique human identification due to its noisy nature. This research focused on investigating the possibilities and limitations of device-free human identification using Wi-Fi RSSI data with machine learning-based classification techniques. To inspect the characteristics of Wi-Fi RSSI data, the authors have conducted statistical analysis techniques. A Kalman filter was applied to minimize the noise in Wi-Fi RSSI data, followed by a feature extraction process. Furthermore, the authors have conducted multiple research experiments in different configurations of receivers and participant numbers. The experimental results show that the human identification accuracy level increases with the number of receivers used for the data collection. Moreover, the authors have identified that human identification accuracy can be further improved by leveraging proper noise reduction methods and feature extraction processes. For a Kalman filter applied and feature-extracted Wi-Fi RSSI dataset of 20 people, the Support Vector Machine (SVM) - Radial Kernel model recorded the highest average accuracy of 99.58%.
Digitalization and Productivity: Evidence from EU Manufacturing Sector

Manufacturing sector productivity is one of main driver for economy grow in Europe. In the context of manufacturing sector digitalization, importance of influencing factors for productivity increase plays a key role. This paper aims to evaluate digitalization impact on EU manufacturing sector productivity, considering variables as relative size measures for the period of 2012-2020. There are strong believe that digitalization is an engine of innovation and competitiveness in manufacturing sector. Changing processes and integration of digital technologies leads manufacturing sector towards productivity increase. We perform OLS regression on sample of 5013 records covering 27 EU countries and 642 manufacturing firms over the years 2012-2020. Analysis consists of such factors as operating revenue, number of employees per company, tangible fixed assets, intangible fixed assets, profit and loss, investment to digitalization. We study ratio of digital investment to total assets as dependent variable to understand how investment decision of company can be evaluated with independent variables, identified in literature review. We build 3 models for regression analysis. Highest value of R-Square calculated for operating revenue as dependent variable is 0.299 and significance level is sufficient. Our results indicate that R-Square is 0.366 for relationship between digital investment and independent variables in analysis. Moreover, intangible assets impact is not significant considering digital investment outlay, which contradict believe stated in literature for direct intangible impact on digitalization. The main variable is number of employees per company with identified significant negative route.
Unsupervised Defect Segmentation in Selective Laser Melting

Obtaining good surface quality in the additive manufacturing process is very challenging as complex physical processes are involved. Although there are deep learning methods proposed to detect defects on surfaces because of the ability of the process to extract features, many of them require a large dataset and hand-labeling work. In this article, we propose an unsupervised segmentation method to detect defects on additive manufactured surfaces, which requires only a single scanned image. The proposed method has three modules, including feature learning, self-attention, and clustering modules, which are responsible for extracting features, capturing global features, and assigning cluster labels. To validate the segmentation performance of the proposed method, experiments were conducted on surfaces fabricated using different materials and different process parameters. The results show that the proposed method segments surface defects effectively compared with other state-of-the-art models.
Finder vi de sprogligt udsatte børn?

Siden 2007 har Danmark haft et obligatorisk, nationalt sprogscreeningsprogram. Denne artikel indledes med et historisk blik på indførelsen af dette tiltag. Dernæst vurderer vi den intensiverede sprogevalueringspraksis på dagtilbudsområdet og i børnehaveklassen og undersøger om tiltaget har haft den ønskede effekt. Sidst men ikke mindst præsenterer vi en sammenligning med praksis i en række andre lande. De tre overordnede spørgsmål vi undersøger, er 1) om sprogscreeningsprogrammet sikrer opsporing af sprogligt udsatte børn , 2) om sprogscreeningsprogrammet sikrer opsporing af børn i risiko for at blive svage læsere , samt 3) om dansk lovgivning og praksis flugter med lovgivning og praksis i andre lande. Resultaterne af vores kortlægning viser ingen indikationer på at det nationale sprogscreeningsprogram har bidraget til opsporing af sprogligt udsatte børn i Danmark, ligesom det heller ikke er lykkedes os at finde nogen indikationer på at det har forbedret danske elevers læsefærdigheder. Danmark synes at være “the-odd-one-out” hvad angår obligatorisk
Evidence-Based Orthopaedic Post-Operative Opioid Prescribing Recommendations Following Sports Medicine Knee Surgery

Over the last two decades, the opioid epidemic in the United States has caused significant harm in terms of illnesses, deaths, and economic costs. To address this public health crisis, healthcare providers must take responsibility for appropriately using and managing these drugs. They should adhere to evidence-based guidelines for prescribing opioids. Several measures have been implemented to reduce excessive opioid use, including Prescription Drug Monitoring Programs, educational campaigns, and multiple pain relief methods. Surgeons, especially those who perform orthopedic and musculoskeletal procedures, have been identified as high-volume opioid prescribers. However, there is a lack of clear guidelines for appropriate opioid dosages and pain management strategies for common sports medicine knee surgeries. Therefore, the aim is to create comprehensive, evidence-based guidelines for postoperative pain relief for such procedures.
Cross-Species Transcriptomics Analysis Highlights Conserved Molecular Responses to Per- and Polyfluoroalkyl Substances

In recent decades, per- and polyfluoroalkyl substances (PFASs) have garnered widespread public attention due to their persistence in the environment and detrimental effects on the health of living organisms, spurring the generation of several transcriptome-centered investigations to understand the biological basis of their mechanism. In this study, we collected 2144 publicly available samples from seven distinct animal species to examine the molecular responses to PFAS exposure and to determine if there are conserved responses. Our comparative transcriptional analysis revealed that exposure to PFAS is conserved across different tissues, molecules and species. We identified and reported several genes exhibiting consistent and evolutionarily conserved transcriptional response to PFASs, such as ESR1, HADHA and ID1, as well as several pathways including lipid metabolism, immune response and hormone pathways. This study provides the first evidence that distinct PFAS molecules induce comparable transcriptional changes and affect the same metabolic processes across inter-species borders. Our findings have significant implications for understanding the impact of PFAS exposure on living organisms and the environment. We believe that this study offers a novel perspective on the molecular responses to PFAS exposure and provides a foundation for future research into developing strategies for mitigating the detrimental effects of these substances in the ecosystem.
Prediction of Successful Spontaneous Breathing Trial and Extubation of Trachea by Lung Ultrasound in Mechanically Ventilated Patients in Intensive Care Unit

Abstract Introduction Spontaneous breathing trial (SBT) is always successful in mechanically ventilated patients. This study was conducted to assess the prediction of successful SBT and extubation of trachea by bedside lung ultrasound in mechanically ventilated patients. Methodology This was a prospective observational study for 1 year conducted at a tertiary teaching hospital ICU on 102 patients with age more than 18 years and who were mechanically ventilated for more than 24 hours. Bedside lung ultrasound was used to assess the lung ultrasound score (LUS) and lung profiles in patients who clinically met the criteria for SBT. The LUS at the beginning of SBT and 30 minutes after SBT were used to predict the successful SBT and tracheal extubation. Result Spontaneous breathing trial and tracheal extubation were successful in 73 (71.6%) and 57 (55.8%) of the patients. The AUC for lung ultrasound in predicting successful SBT at the beginning and 30 minutes of SBT were 0.781 (CI 95% 0.674–0.888, p < 0.001) and 0.841 (CI 95% 0.742–0.941, p < 0.001) with a cut-off value of 17.5 and 19.5, respectively. Similarly, AUC for LUS in relation to tracheal extubation was 0.786 (CI 95% 0.694–0.879, p < 0.001) and 0.841(CI 95% 0.756–0.925, p < 0.001) at 0 and 30 minutes. About 57.5% of the patients with A profiles tolerated successful SBT while 48.3% of the patients having C profile had failed SBT (p < 0.001). COPD, lung ultrasound, higher SOFA score, and longer duration of mechanical ventilation had a statistically significant negative correlation with successful SBT. Conclusion Lower LUS and A profiles lung ultrasound are associated with more successful weaning and tracheal extubation in mechanically ventilated patients. How to cite this article Rajbanshi LK, Bajracharya A, Devkota D. Prediction of Successful Spontaneous Breathing Trial and Extubation of Trachea by Lung Ultrasound in Mechanically Ventilated Patients in Intensive Care Unit. Indian J Crit Care Med 2023;27(7):482–487.
Composition, Diversity and Sex-Related Differences in Intestinal Microbiota in Captive African Penguins (Spheniscus demersus)

Simple Summary The African penguin (Spheniscus demersus) is an endangered species. Currently, the intestinal microbiota of African penguins remain uninvestigated. An understanding of the microbial communities in African penguins could provide valuable information for saving this species. Using high-throughput sequencing, we evaluated the composition and diversity of the intestinal microbiota in captive African penguins. Proteobacteria, Actinobacteria and Firmicutes were the predominant bacteria in the intestinal microbiota of captive African penguins. The sex-related differences in microbiota in African penguins were also explored. Female and male African penguins had similar microbial diversities. However, a notable sex-related difference was found between their microbial compositions. Female African penguins have a higher abundance of Pseudomonas (a common avian pathogen) than males. Our data suggest that the intestinal microbiota of female African penguins are more unstable than the intestinal microbiota of males in captivity. The intestinal health of female African penguins might require more care in captive management. Abstract An understanding of the microbial communities in African penguins (Spheniscus demersus) could provide valuable information for saving this endangered species. The objective of this study was to investigate the composition, diversity and sex-related differences in the intestinal microbiota of captive African penguins. Fecal samples were collected from 21 captive adult African penguins reared in the same conditions at Shanghai Zoo. The results show that Proteobacteria, Actinobacteria and Firmicutes were the predominant bacteria in the intestinal microbiota of the captive African penguins. No difference was found in microbial diversity between female and male African penguins, as shown by their similar alpha and beta diversities. However, a notable sex-related difference was found between their microbial compositions. Female African penguins have a higher abundance of Pseudomonas and a lower abundance of Kocuria than males. A functional prediction indicates that the “mRNA surveillance pathway”, “Polyketide sugar unit biosynthesis”, “Wnt signaling pathway”, “Lysosome” and “Cell cycle” pathways were significantly enriched in the microbiota of female African penguins. In conclusion, the present study indicates that the compositions and predicted functions of the intestinal microbiota are significantly different between the sexes. Our data suggest that the intestinal microbiota of female African penguins are more unstable than the intestinal microbiota of males in captivity.
Randomness evaluation of key generation based on optical OFDM system in visible light communication networks

Recently, the authors proposed a physical-layer key generation scheme for optical orthogonal frequency division multiplexing (OFDM) techniques in an indoor scenario. The key generation protocol exploits bipolar and real-valued optical OFDM samples to create confidential keys. It determines a chunk of cyclic prefix samples positioned in the space of small channel impact to generate the confidential keys during the session duration. This key-generation approach offers strong computational security to counter passive eavesdroppers and key creation on the fly, with zero bit-mismatch rates. In this Letter, the authors evaluate the randomness of the confidential keys produced from the recently proposed key-generation protocol to validate if the keys are truly random. The authors apply a statistical test suite of the National Institute of Standards and Technology to test randomness. The results demonstrate that the keys generated from the proposed key generation system pass all the tests. The results also demonstrate that the proposed key generation system provides uncorrelated keys with an approximately equal probability of bits (discrete uniform distribution) on an average, which yields a high security system against statistical attacks.
Enhanced deep soft interference cancellation for multiuser symbol detection

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model‐based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data‐driven methods perform slightly worse than model‐based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning‐based method by improving a state‐of‐the‐art data‐driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error‐propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model‐based methods in perfect CSI environments and the best performance in imperfect CSI environments.
Analysis of the propensity of Italian and German forest owners towards forest certification for ecosystem services

: This study analyses the perception of the relationship between forest certification and the production of eco-system services by Programme for the Endorsement of Forest Certification (PEFC) and Forest Stewardship Council (FSC) sustainable forest management (SFM) certification holders. In addition, the psychological constructs that govern the use of certification for ecosystem services are investigated. Specifically, online questionnaire surveys were submitted to a sample of Italian and German forest owners and managers to study reasons for and against and global motives to adopt certification for ecosystem services through the application of Behavioural Reasoning Theory (BRT). Results show that respondents believe that certification can better support ecosystem services related to 'regulation and maintenance' and the conservation of biodiversity. On the other hand, the application of BRT has only been partially useful in explaining the psychological factors towards the adoption of ecosystem services certifications. In any case, attitudes and reasons for certainly had a significant influence on the intention to adopt certifications. Apart from the scientific implications, these results have practical applications for policymakers who can focus on the dissemination of the certification of ecosystem services by trying to support through eco-policies, the attitudes and reasons for expressed by forest owners.
Unsteady Magnetohydrodynamic Free Convective Flow Fast a Semi-finite Vertical Porous Flate

In this article, we studied the effects of variable viscosity and thermal conductivity on an unsteady two-dimensional laminar flow of a viscous incompressible electrically conducting fluid past a semi-infinite vertical plate taking into account the mass transfer. The fluid viscosity is assumed to vary as a linear function of temperature. The governing equations for the flow are transformed into a system of non-linear ordinary differential equations are solved by a perturbation technique. The effects of the various parameters on the velocity, temperature, concentration and skin-friction profiles are presented graphically and discussed qualitatively.