Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutational Analysis and Deep Learning Classification of Uterine and Cervical Cancers

We analyzed tumor mutations of 7 uterine and 2 cervical cancers with the goal of developing a Deep Learning (DL) software tool that can automatically classify tumors based on their somatic mutations. The data were obtained from the AACR Genie Project [1], that has a collection of more than 120,000 tumor samples for more than 750 cancer types. We performed a thorough analysis of the mutational data of tumors of the uterus and uterine cervix, selecting tumors with 3 or more mutations and cancer types with more than 15 cases. For each cancer type we then selected the top 12 most mutated genes among their neoplasms. In the introduction section we summarize our analysis of these nine diseases and in the deep learning section we present a convolutional neural network (CNN) [2] that yields an overall classification accuracy of 94.3% and 89.2% on the train and test datasets, respectively. We hope that this tool can be added to the existing arsenal of histological and immunohistochemical techniques in cases when a precise diagnosis cannot be clearly determined. Each cancer type has a unique somatic mutational profile that can be used to disambiguate two candidate malignancies with similar histologic features.
Investigating Students' Behavioral Intention Towards Adoption of Mobile Learning in Higher Education Institutions of Pakistan

investments and remarkable changes in every field of life. Institutions today are now operating in a highly volatile environment, which is changing rapidly being characterized by uncertainty. The new technological era is abound with numerous opportunities and challenges for the educational system across the globe. Educational institutions have been revolutionized as learning changes are elicited by changes in technology [i]. Universities today have incorporated technology in their strategic goals, making it a substantial part of every university's budget [ii]. The technological revolution, with the introduction of 3G/ 4G mobile technologies has helped in capacity building and enhancement of faster communication and information sharing being technology enabled. Resultantly technological change has transformed the traditional ways of learning giving way to Distance learning (Dlearning), Electronic Learning (E-learning) and Mobile learning (M-learning). M-learning offers an opportunity for self-study by allowing easy access to learning resources and exchange of information and feedback with the instructors [iii]. The impact of technology on society has changed overall life processes but its impact on learning and diffusion in the educational activities need to be observed with the focus on the user's readiness and acceptance of the new technology. Reluctance of users to accept the latest technology can lead to structural catastrophe and result in no benefit for the institutions [iv-v]. The opportunities and benefits offered by Mlearning have not been explored completely [iv]. To ascertain the efficient use of an institute's time and financial resources devoted towards M-learning, it was essential to analyze the determinants influencing students' acceptance of M-learning before its effective deployment in higher education institutes of Pakistan. This study was conducted by applying the UTAUT model to find out the determinants as well as the effect of age and gender on the acceptance of M-learning [v]. The study would help the management to analyze and assess whether mobile technologies, with the aid of the new emerging 3G/ 4G, can become
Are Neural Bug Detectors Comparable to Software Developers on Variable Misuse Bugs?

Debugging, that is, identifying and fixing bugs in software, is a central part of software development. Developers are therefore often confronted with the task of deciding whether a given code snippet contains a bug, and if yes, where. Recently, data-driven methods have been employed to learn this task of bug detection, resulting (amongst others) in so called neural bug detectors. Neural bug detectors are trained on millions of buggy and correct code snippets. Given the “neural learning” procedure, it seems likely that neural bug detectors – on the specific task of finding bugs – have a performance similar to human software developers. For this work, we set out to substantiate or refute such a hypothesis. We report on the results of an empirical study with over 100 software developers, targeting the comparison of humans and neural bug detectors. As detection task, we chose a specific form of bugs (variable misuse bugs) for which neural bug detectors have recently made significant progress. Our study shows that despite the fact that neural bug detectors see millions of such misuse bugs during training, software developers – when conducting bug detection as a majority decision – are slightly better than neural bug detectors on this class of bugs. Altogether, we find a large overlap in the performance, both for classifying code as buggy and for localizing the buggy line in the code. In comparison to developers, one of the two evaluated neural bug detectors, however, raises a higher number of false alarms in our study.
Understanding Brand Trust in the Context of Consumer Reshoring Sentiment: An Experimental Study

This study focuses on the demand-side effects of reshoring and an experimental study was conducted to understand the mediator role of consumer reshoring sentiment among consumers’ ethnocentric orientation and brand trust under the conditional effects of perceived motives and category country image. In addition, the model has been tested for partial and full reshoring conditions. The findings exhibit consumers’ ethnocentric orientation interacts with perceived motive, generates a reshoring sentiment, which intersect with the category image of the offshored country, ultimately produces brand trust accordingly.
The Study of Consumers’ Intention to Purchase in Unmanned Stores

With the advancement of the technology era, the technology of various industries has gradually developed rapidly. The type of shopping that people pursue has also changed with time. From the grocery store gradually stepping into the supermarket, convenience stores have been gradually introduced to Taiwan and have slowly flourished in Taiwan because of the high desire of people to pursue a higher quality of life. In the case of an unmanned store, we focused on the X-Store, a 7-11 unmanned store in Taiwan, in which the development goals were to explore, experience, and excellent. We applied the Extended Integrated Technology Acceptance Model (UTAUT2) to conduct research on consumers’ intentions toward unmanned stores, and we retrieved 180 valid questionnaires online. From the research results, it was found that "performance expectancy", "effort expectancy", "social influences", "facilitating conditions", "behavioral intention" and "use behavior" would affect consumers’ intentions for unmanned shops. “social influences” as the independent variable and “use intention” as the dependent variable. The results show that at the level of α = 0.05, “social influences” has a positive and significant relationship with “use intention”. The T value
Exploring Classroom Motivation Using Alderfer’s Theory

Numerous research has explored that human motivations affect learning outcomes significantly. The main aim of the research was to explore the classroom motivations of undergraduate students from the Faculty of Administrative Science and Policy Studies, Universiti Teknologi MARA through the lens of the Alderfer theory of motivation. In particular, the main objective of the study was to determine how the Alderfer theory, existence, relatedness, and growth influence students’ classroom motivation. The research has adopted a correlational and cross-sectional study approach. A total of 424 undergraduate students from 5 academic programs the Administrative Science and Policy Studies participated in the online survey. The questionnaire consisted of 5 sections with 24 items on Alderfer’s three components of Existence, Relatedness and Growth. The study’s findings show that Existence, Affective and Growth dimensions scored from moderate to high mean scores ranging from 3.5 and above. The correlation analysis shows a strong significant relationship between existence and growth r =. 711, p=. 000. While a weak positive relationship between existence and relatedness r=. 307, p=. 000 and growth and relatedness r= . 150, p=. 002. The study’s implication indicates that most undergraduate students a moderate high level of motivation. Hence, to sustain the classroom motivation of the students, continuous psychological, materials and academic support together with training in teaching pedagogy are vital to ensure their academic success. personality, lack self -belief in their abilities and face problems adapting to the learning techniques at Higher Education Institutions. The respondents in this study are Faculty of Human Resource Management and Development students whose CGPA is less than 2.5. Data were collected through questionnaires, and the responses were analysed descriptively using the Statistical Package for Social Sciences (Norhani et al., 2005). Therefore, this study showed that students' lack of self-belief in their abilities and face problems in adapting to the learning techniques at Higher Education Institutions lead to poor academic performance. Another past study proves that learning self-regulation and motivation have a significant relationship with student academic achievement. Therefore, students can maintain a level of motivation while mastering self-learning skills to maintain academic achievement at a high level. Students who have a high level of motivation can have a good effect on their academic achievement and successfully adapt to changes in learning. This study uses a quantitative approach based on a survey design. The random sampling method used a total of 240 undergraduate students from the Faculty of Education, UKM was selected as the study sample. The research instrument adapted the questionnaire from the Motivated Strategies for Learning Questionnaire (MSLQ). The Cumulative Grade Point Average (CGPA) is used to measure the level of student academic achievement (Nuraisyah Faridah,
Analysis of the Interactions between Inflation and Stock Prices in Ghana

This paper examines the relationship between inflation and stock prices in Ghana in order to assist businesses and individuals to make informed decisions when the inflation rate changes. A quantitative approach was adopted using monthly time series data from July 2007 to December 2019. The results of the unit root test revealed that the series were non-stationary at the levels but became stationary after the first difference. The results from the Multiple Regression Analysis carried out with Eviews 7.0 econometric software revealed a direct relationship between inflation and stock prices in the Ghanaian context (β = 0.762, p < 0.05). The study recommends that the central bank implement measures to keep inflation at low levels so that it does not erode the value of returns on investment in order to increase public confidence in the stock market.
Caffeine in liver diseases: Pharmacology and toxicology

We have previously shown that adenosine A1AR antagonists, adenosine A2aAR antagonists, and caffeine have significant inhibitory effects on the activation and proliferation of hepatic stellate cells in alcoholic liver fibrosis. Many recent studies have found that moderate coffee consumption is beneficial for various liver diseases. The main active ingredient of coffee is caffeine, which is a natural non-selective adenosine receptor antagonist. Moreover, numerous preclinical epidemiological studies and clinical trials have examined the association between frequent coffee consumption and the risk of developing different liver diseases. In this review, we summarize and analyze the prophylactic and therapeutic effects of caffeine on various liver diseases, with an emphasis on cellular assays, animal experiments, and clinical trials. To review the prevention and treatment effects of caffeine on different liver diseases, we searched all literature before 19 July 2022, using “caffeine” and “liver disease” as keywords from the PubMed and ScienceDirect databases. We found that moderate coffee consumption has beneficial effects on various liver diseases, possibly by inhibiting adenosine binding to its receptors. Caffeine is a potential drug for the prevention and treatment of various liver diseases.
The application of gargle containing honeysuckle and semen oroxyli to reduce the pain and complications after uvulopalatopharyngoplasty

Purpose: The main purpose of this pilot study was to detect the positive effects of our self-made gargle containing honeysuckle and semen oroxyli on post-operative pain and complications after Uvulopalatopharyngoplasty (UPPP). Methods: Patients with obstructive sleep apnea (OSA) who had underwent elective UPPP during the period of April 2019 to January 2022 were randomly divided into treatment group and control group. The patients in the treatment group were instructed to gargle the solution containing honeysuckle and semen oroxyli (25 ml) four times a day for 2 weeks. The patients in the control group were instructed to gargle normal saline (25 ml) at the same schedule. The post-operative resting throat pain, swallowing throat pain and patient comfort level were evaluated at 12 h, 1 week and 2 weeks after UPPP. The post-operative complications were collected and analyzed. Results: During the study period, 218 patients completed all the post-operative assessments. For resting throat pain, the treatment group had much lower VAS scores at 1 week and 2 weeks after UPPP. For swallowing throat pain, treatment group had much lower VAS scores than control group at 2 weeks after surgery. And patients in the treatment group felt more comfortable comparing to those in control group at 1 week and 2 weeks after UPPP. Although the treatment group had less numbers of patients with post-operative wound infection or bleeding, the difference between the 2 groups was not statistically significant. Conclusion: The gargle containing honeysuckle and semen oroxyli could relieve both resting and swallowing throat pain and increase patient comfort after UPPP.
OBSERVATIONAL LIMITS ON THE SPIN-DOWN TORQUE OF ACCRETION POWERED STELLAR WINDS

The rotation period of classical T Tauri stars (CTTS) represents a longstanding puzzle. While young low-mass stars show a wide range of rotation periods, many CTTS are slow rotators, spinning at a small fraction of breakup, and their rotation period does not seem to shorten, despite the fact that they are actively accreting and contracting. Matt & Pudritz proposed that the spin-down torque of a stellar wind powered by a fraction of the accretion energy would be strong enough to balance the spin-up torque due to accretion. Since this model establishes a direct relation between accretion and ejection, the observable stellar parameters (mass, radius, rotation period, magnetic field) and the accretion diagnostics (accretion shock luminosity) can be used to constrain the wind characteristics. In particular, since the accretion energy powers both the stellar wind and the shock emission, we show in this Letter how the accretion shock luminosity LUV can provide upper limits to the spin-down efficiency of the stellar wind. It is found that luminous sources with LUV ⩾ 0.1 L☉ and typical dipolar field components <1 kG do not allow spin equilibrium solutions. Lower luminosity stars (LUV ≪ 0.1 L☉) are compatible with a zero-torque condition, but the corresponding stellar winds are still very demanding in terms of mass and energy flux. We therefore conclude that accretion powered stellar winds are unlikely to be the sole mechanism to provide an efficient spin-down torque for accreting CTTS.
The neural coding of tonal working memory load: An functional magnetic resonance imaging study

Tonal working memory load refers to the number of pitches held in working memory. It has been found that different verbal working memory loads have different neural coding (local neural activity pattern). However, whether there exists a comparable phenomenon for tonal working memory load remains unclear. In this study, we used a delayed match-to-sample paradigm to evoke tonal working memory. Neural coding of different tonal working memory loads was studied with a surface space and convolution neural network (CNN)-based multivariate pattern analysis (SC-MVPA) method. We found that first, neural coding of tonal working memory was significantly different from that of the control condition in the bilateral superior temporal gyrus (STG), supplement motor area (SMA), and precentral gyrus (PCG). Second, neural coding of nonadjacent tonal working memory loads was distinguishable in the bilateral STG and PCG. Third, neural coding is gradually enhanced as the memory load increases. Finally, neural coding of tonal working memory was encoded in the bilateral STG in the encoding phase and shored in the bilateral PCG and SMA in the maintenance phase.
Supernova explosions in magnetized, primordial dark matter haloes

The first supernova explosions are potentially relevant sources for the production of the first large-scale magnetic fields. For this reason we present a set of high resolution simulations studying the effect of supernova explosions on magnetized, primordial halos. We focus on the evolution of an initially small-scale magnetic field formed during the collapse of the halo. We vary the degree of magnetization, the halo mass, and the amount of explosion energy in order to account for expected variations as well as to infer systematical dependencies of the results on initial conditions. Our simulations suggest that core collapse supernovae with an explosion energy of 10^51 erg and more violent pair instability supernovae with 10^53 erg are able to disrupt halos with masses up to a about 10^6 and 10^7 M_sun, respectively. The peak of the magnetic field spectra shows a continuous shift towards smaller k-values, i.e. larger length scales, over time reaching values as low as k = 4. On small scales the magnetic energy decreases at the cost of the energy on large scales resulting in a well-ordered magnetic field with a strength up to ~ 10^-8 G depending on the initial conditions. The coherence length of the magnetic field inferred from the spectra reaches values up to 250 pc in agreement with those obtained from autocorrelation functions. We find the coherence length to be as large as $50\%$ of the radius of the supernova bubble. Extrapolating this relation to later stages we suggest that significantly strong magnetic fields with coherence lengths as large as 1.5 kpc could be created. We discuss possible implications of our results on processes like recollapse of the halo, first galaxy formation, and the magnetization of the intergalactic medium.
Brain metastasis from gastric adenocarcinoma: A large comprehensive population-based cohort study on risk factors and prognosis

Aims Although brain metastasis from gastric adenocarcinoma (GaC) is rare, it may significantly affect survival and quality of life. The aim of this large, comprehensive, population-based cohort investigation was to investigate factors that were associated with brain metastasis from GaC and to explore the prognostic factors and time-dependent cumulative mortalities among cases with GaC and brain involvement. Methods Population-based information on cases with GaC diagnosed from 2010 to 2016 was obtained from a large-scale database. Factors that were associated with brain metastasis were investigated utilizing multivariable logistic regression. Time-dependent tumor-specific mortalities of cases with GaC and brain involvement were then computed utilizing the cumulative incidence functions (CIFs), and mortalities were compared between subgroups utilizing Gray’s test. Factors that were associated with death were further evaluated utilizing multivariable Fine–Gray subdistribution hazard regression. Results Together, 28,736 eligible cases were included, which comprised 231 (1%) cases with brain metastasis and 10,801 (38%) with metastasis to other sites, encompassing a follow-up of 39,168 person-years. Brain metastasis occurred more often among younger patients (within overall cancers), in cases with stomach cardia tumors, within cases with signet-ring cell carcinoma (within overall cancers), and within cases with positive lymph nodes (within overall tumors); it was less often detected among black people. Brain involvement was associated with more lung and bone metastases. The median survival time of cases having brain metastasis was only 3 months; the 6- and 12-month tumor-specific cumulative mortalities were 57% and 71%, respectively. Among cases with GaC and brain metastasis, those with gastric cardia cancers (when receiving radiotherapy), those undergoing resection, and those receiving chemotherapy had lower mortality risks, while younger patients (when receiving chemotherapy or radiotherapy) and people with positive lymph nodes (when receiving radiotherapy) had higher death hazards. Conclusion Among patients with GaC, brain metastasis was correlated with several clinical and pathological variables, including ethnicity, age, cancer histology, location, lymph node involvement, and metastases to other sites. Cases having brain metastasis had poor survival that was correlated with age, cancer location, lymph node metastasis, and management. These findings offer vital clues for individualized patient care and future mechanistic explorations.
Maternal homework approach and adolescents’ academic skills: The mediating role of task values

The present study investigated the mediating role of the task values between the types of maternal homework approach (perceptions of their child’s autonomy or direct involvement) and adolescents’ academic skills. Data were utilized from 995 mother–child dyads followed across Grades 6, 7, and 9. At each time-point, mothers answered questionnaires on the types of their homework approach, adolescents answered questionnaires about their task values for math and Finnish, and adolescents’ skills in math (arithmetic and multiplication) and reading (reading fluency and reading comprehension) were tested. Separate longitudinal structural equation models were estimated for math and for reading. The results showed, first, that maternal perceptions of their adolescents’ autonomy positively predicted adolescents’ task values but did not predict skills. Second, maternal direct involvement in homework completion negatively predicted adolescents’ math and reading skills but did not predict task values. Finally, concerning the effect of task values between homework approach and skills, task values in Grade 7 played a role in the associations between perceptions of autonomy (but not direct involvement) in Grade 6 and adolescents’ skills in Grade 9. Overall, the present study highlights the importance of student autonomy with regard to homework in promoting adolescents’ task values as well as the role of adolescents’ task values in the associations between maternal perceptions of autonomy and the development of adolescents’ math and reading skills.