Miracle-dz/UniFAR-FTUs huggingface dataset:
Endomorphin-2 Analog Inhibits the Growth of DLD-1 and RKO Human Colon Cancer Cells by Inducing Cell Apoptosis

Background In developed countries, colon cancer is a leading cause of cancer-associated mortality. Dietary changes have resulted in an increased incidence of colon cancer in Asia. This study aimed to investigate the effects of the structural analog of endomorphin-2 (H-Tyr-Pro-Phe-Phe-NH2) on human colon cancer cells in vitro. Material/Methods Human DLD-1 and RKO colon cancer cells and CCD-18Co normal human colonic fibroblasts were treated with increasing doses of the structural analog of endomorphin-2. Cells underwent the MTT assay, fluorescence confocal flow cytometry, and Hoechst 33258 staining to investigate cell proliferation, the cell cycle, and apoptosis. Western blot was used to measure the expression levels of poly(ADP-ribose) polymerase-1 (PARP-1), cytochrome c, caspase-3, and caspase-9. The 2′,7′-dichlorofluorescein diacetate (DCFH-DA) fluorescence method measured reactive oxygen species (ROS). Results Cell proliferation of DLD-1 and RKO cells was inhibited by the endomorphin-2 analog in a dose-dependent manner, and a 100 μM dose reduced DLD-1 and RKO cell proliferation by 28% and 23%, respectively, at 72 h. Endomorphin-2 analog induced cell apoptosis and the generation of ROS, activated caspase-3 and caspase-9, and increased the levels of p53 and cytochrome c release, and down-regulated of Akt activation in DLD-1 and RKO cells in a dose-dependent manner. Treatment of the DLD-1 and RKO cells with the endomorphin-2 analog increased the expression of Bax and reduced the expression of Bcl-2. Conclusions Endomorphin-2 analog inhibited colon cancer cell proliferation, activated apoptosis, and down-regulated Akt phosphorylation of human DLD-1 and RKO colon cancer cells in vitro in a dose-dependent manner.
UGEMM: Unary Computing Architecture for GEMM Applications

General matrix multiplication (GEMM) is universal in various applications, such as signal processing, machine learning, and computer vision. Conventional GEMM hardware architectures based on binary computing exhibit low area and energy efficiency as they scale due to the spatial nature of number representation and computing. Unary computing, on the other hand, can be performed with extremely simple processing units, often just with a single logic gate. But currently there exist no efficient architectures for unary GEMM.In this paper, we present uGEMM, an area- and energy-efficient unary GEMM architecture enabled by novel arithmetic units. The proposed design relaxes previously-imposed constraints on input bit streams—low correlation and long stream length— and achieves superior area and energy efficiency over existing unary systems. Furthermore, uGEMM’s output bit streams exhibit higher accuracy and faster convergence, enabling dynamic energy-accuracy scaling on resource-constrained systems.
Productive Capabilities and Economic Development: A Case for Industrial Diversification in Pakistan

The central argument of our paper is that a country’s long-term economic development depends upon its productive capabilities and the types of products it produces and exports. The East Asian countries (EACs), realising the importance of a clear long-term vision of industrial and technological catch-up with the developed world, designed their industrial policies accordingly. Thus, these countries gradually moved up the industrial ladder and developed capabilities for the production of more complex and sophisticated products. This, in our view, significantly contributed towards their phenomenal economic performance. The recent literature on the Product Space and Economic Complexity empirically support this logic of economic development through industrial diversification. This stream of literature also shows that the ability of a country to diversify its exports critically depends upon the kinds of industries that country specialises in. We have shown that Pakistan has failed to realise the importance of a long-term vision which involves industrial and technological catch up with developed countries. It is argued that protection of rent-seeking and uncompetitive industries, lack of performance oriented incentives to industrial sector, and failure to achieve industrial development targets, contributed in fostering an unsophisticated industrial structure. These have been the fundamental reasons for Pakistan’s inability to diversify its export structure into higher value-added products; thus, resulting in an unstable economic growth. Our preliminary econometric analysis reveals that higher political instability in Pakistan, which can be seen as an indicator of discontinuity in economic policies and absence of a long-term vision, is found to be negatively associated with ECI in the long run. Liberal trade policies are also found to be negatively affecting ECI in the long run. Therefore, we argue that Pakistan’s economic policies should be guided by a long term vision of developing productive and technological capabilities in sectors where there is a higher scope for diversification as well as innovation.
PMEvo: portable inference of port mappings for out-of-order processors by evolutionary optimization

Achieving peak performance in a computer system requires optimizations in every layer of the system, be it hardware or software. A detailed understanding of the underlying hardware, and especially the processor, is crucial to optimize software. One key criterion for the performance of a processor is its ability to exploit instruction-level parallelism. This ability is determined by the port mapping of the processor, which describes the execution units of the processor for each instruction. Processor manufacturers usually do not share the port mappings of their microarchitectures. While approaches to automatically infer port mappings from experiments exist, they are based on processor-specific hardware performance counters that are not available on every platform. We present PMEvo, a framework to automatically infer port mappings solely based on the measurement of the execution time of short instruction sequences. PMEvo uses an evolutionary algorithm that evaluates the fitness of candidate mappings with an analytical throughput model formulated as a linear program. Our prototype implementation infers a port mapping for Intel's Skylake architecture that predicts measured instruction throughput with an accuracy that is competitive to existing work. Furthermore, it finds port mappings for AMD's Zen+ architecture and the ARM Cortex-A72 architecture, which are out of scope of existing techniques.
Determinant Factors Affecting the Number of Visitors in Recreational Parks in Ethiopia: The Case of Addis Ababa Recreational Parks

This study was conducted to determine factors affecting the number of visitors in recreational parks in Addis Ababa. The study encompasses the analysis of the data collected from 180 randomly selected sample visitors of Hamle 19 and Future recreational parks selected purposively selected from Addis Ababa recreation sites. Both descriptive statistics and econometrics model were used to analyze the quantitative data. To determine the factors influencing the number of visitors to the recreational parks econometric model called multiple regression model used. To analyze the data a statistical software known as SPSS used. The mean of age of visitors to the recreational parks were 31 years with minimum of 18 and maximum of 59. And the average family size was 3.6 while the minimum and the maximum household size were 1 and 10 respectively. Travel costs, visitor’s income and acquaintance with the site were found to be significant of a recreation demand at Addis Ababa recreation sites. Whereas other explanatory variables such as Gender, marital status, group visit and occupation, were found to be insignificant of visits to Addis Ababa recreation site. Among the other variables, visitors’ monthly income is considered as one of the critical variables that affects the number of visits positively. As the income of the visitors’ increases by one birr, the number of visits is expected to increase by 0.00193 percent.
Identifying the relation between author gender and Dutch suspense novels

In this research, the relation between author gender and the text of suspense novels is explored. Novels have been classified on author gender before, but with a main focus on the identification of author gender (Koppel et al., 2002). It is important to control variables in the corpus and not to overgeneralise results when using NLP techniques to research the relation between gender and text (Koolen & Van Cranenburgh, 2017). Therefore, this research will focus on novels within one genre, namely Dutch suspense novels.
On a correct diet: exploration of the orthorexia construct from the essential nuclei of experimental discourse

Abstract Objectives: To explore the experience lived by some women who are concerned with following a natural and organic diet. Method: The qualitative analysis of the discourse was done as a bricolage (thematic content analysis and phenomenological interpretative analysis, using different ad hoc techniques). Results: The subjective experience of women consists of a phenomenological field that defines their historicity: past, represented by the theme "Why did you choose to eat like this"; present, "An optimism recreated"; and imagined future, "Absence of disease as object of ideal consciousness". This phenomenological field evolves, in experience and discourse, as an intermittent dilation of the theme "The expansion of consciousness in the right appetite". Conclusions: The orthorexia construct and the correct appetite discourses should be explored in greater depth by the scientific community in order to investigate: social stigmatization of people concerned with healthy eating and, in an associated way, pathologization of condition.
Functional Annotations of Single-Nucleotide Polymorphism (SNP)-Based and Gene-Based Genome-Wide Association Studies Show Genes Affecting Keratitis Susceptibility

Background Keratitis is a complex condition in humans and is the second most common cause of legal blindness worldwide. Material/Methods To reveal the genomic loci underlying keratitis, we performed functional annotations of SNP-based and gene-based genome-wide association studies of keratitis in the UK Biobank (UKB) cohort with 337 199 subjects of European ancestry. Results The publicly available SNP-based association results showed a total of 34 SNPs, from 14 distinct loci, associated with keratitis in the UKB. Gene-based association analysis identified 2 significant genes: IQCF3 (p=2.0×10−6) and SOD3 (p=2.0×10−6). Thirty-two candidate genes were then prioritized using information from multiple sources. The overlap of IQCF3 in these 2 analyses resulted in a total of 33 hub genes. Functional annotation of hub genes was performed and transcriptional factors of IQCF3 and SOD3 were predicted. Conclusions A total of 34 SNPs from 14 distinct loci were identified as being associated with keratitis, and 32 candidate genes were then prioritized. In addition, IQCF3 and SOD3 were identified by their p values through gene-based tests on the basis of individual SNP-based tests. The functional relationship between these suspect genes and keratitis suggest that IQCF3 and SOD3 are candidate genes underlying keratitis.
Department of Economics- FEA/USP

This paper provides evidence on a large-scale teacher incentive program in the state of São Paulo, Brazil, which awarded group bonuses to teachers and school staff conditional on improvements in student performance. By using a difference-in-differences and triple-differences framework, I show that the program had overall positive effects on student achievement, although improvements vary across grades and subjects. The robustness of the results is assessed through the use of a series of alternative counterfactuals. I also investigate whether initial school characteristics affect the impact of the program. Although it could be expected that free-riding effects increase with the number of teachers in schools, therefore limiting the impact of the program, this does not seem to be the case. More sizeable differences are found according to school’s previous performance. Initially low-performing schools improved much more than the average, suggesting there may be considerable differences in the ability of schools to respond to this type of policy.
Risky Lifestyle Choices of Women with Breast Cancer

Using data from the Panel Study of Income Dynamics on breast cancer diagnosis and lifestyle choices, we estimate how being diagnosed influences smoking, drinking, and exercising habits for more than 8, 000 women over the period 1999 to 2011. Controlling for unobserved heterogeneity, persistence in potentially addictive behaviors, and correlation across behaviors, we find that the impact of a diagnosis has a different effect on smoking, drinking, and exercising behavior. Furthermore, the impact depends upon the recency of the diagnosis. Recently diagnosed women exercise and smoke less but do not change their drinking habits relative to healthy women. Our approach provides insight into what extent women who are faced with negative information about life expectancy take this into consideration when deciding to engage in risky behaviors that might further affect their survival in a significant way.
Investigating The Acute Levodopa Response In Early To Advanced Parkinson’s Disease

Parkinson’s disease (PD) is a neurogenerative movement disorder that often requires surgical interventions such as deep brain stimulation (DBS) when motor complications arise from long term levodopa therapy. Understanding the level of motor improvement received by patients from levodopa (levodopa response; LR) at each stage of disease duration is integral to optimizing both current treatment and DBS implementation. In this study, the levodopa challenge test was employed to investigate the LR in early to advanced stages of disease in 70 PD participants. The LR only moderately correlated with disease duration, suggesting large interindividual variability in the LR between patients of similar disease durations. The LR correlated most strongly with motor symptom severity in the OFFmedication state. We proposed that this was in part due to whether an individual relies more heavily on a nigral or extra-nigral control of dopamine in the PD brain. These findings offer support for implementing DBS in individuals earlier in disease and with smaller motor responses to levodopa.
War of Minds among Young Adults: A Psychological Perspective

The intra-psychic conflicts in the minds of youth are detrimentally affecting their physical & psychological health. The existential anxiety of what life is, what to do after getting a degree, what's the meaning of life, etc is shattering their equilibrium. The gap between the knowledge they are receiving from schools & colleges and their virtual life is expanding day by day. Our present education and training systems do not provide young people with the basic skills needed to have a fulfilling and satisfied life, and they are continuously receiving formal education.Conflicts and wars do not only represent the physical aggression but it also includes the conflicts running in psyche of individual which at first place give birth to any kind of violence or war. It all starts with unbridled emotions, distorted cognitions, the maladaptive thinking patterns, the differences between the proficiency they are receiving and the actual problems they are facing, highlights the need of better educational system in life. The existential vacuum of their life makes them troublesome rather than troubled leading to psychopathology, anti-social and futile behavior.Thus, change of mind is the need of hour and non-formal education should not be seen as an alternative to formal education, but rather recognized for its complementariness in providing a more holistic and skills based approach, equipping youth to meet the competing demands of work and personal life. Young adulthood is an important period for the development of preventive interventions which should be designed to prevent the development of more serious psychopathology in adulthood. The present paper explores the conflicts in the psyche of individuals which may give birth to all kinds of violence and also suggest importance of life skills development for eradicating the war of values among youth.
Curbing Illicit Financial Flows from Resource-rich Developing Countries: Improving Natural Resource Governance to Finance the SDGs Commodity Trade-related Illicit Financial Flows: Evidence of Abnormal Pricing in Commodity Exports from Ghana

Cross-border illicit financial flows (IFFs) via misinvoicing of international trade has emerged as a prominent challenge for resource-rich developing countries aiming to increase domestic resource mobilisation to finance their Sustainable Development Goals. However, there is a lack of robust evidence and empirical methodologies to analyse the magnitude of trade misinvoicing from developing countries. In this paper, we identify IFF risks in the Ghanaian gold and cocoa sectors before using transaction-level data on commodity exports to provide novel evidence of abnormal pricing, defined as the magnitude of trade valued outside an estimated arm’s length price range. We find that the undervalued exports for gold equalled 10% of its total export value between 2011-17. Similarly, we estimate that 1% of total cocoa beans and 7.2% of cocoa paste exported within the same period were undervalued. These findings corroborate our analysis of IFF risks in each industry as well as limited existing evidence of IFFs via commodity trading from Ghana.
Edge-Assisted Distributed DNN Collaborative Computing Approach for Mobile Web Augmented Reality in 5G Networks

Web-based DNNs provide accurate object recognition to the mobile Web AR, which is newly emerging as a lightweight mobile AR solution. Webbased DNNs are attracting a great deal of attention. However, balancing the UX against the computing cost for DNN-based object recognition on the Web is difficult for both self-contained and cloud-based offloading approaches, as it is a latency-sensitive service but also has high requirements in terms of computing and networking abilities. Fortunately, the emerging 5G networks promise not only bandwidth and latency improvement but also the pervasive deployment of edge servers which are closer to the users. In this article, we propose the first edge-based collaborative object recognition solution for mobile Web AR in the 5G era. First, we explore the finegrained and adaptive DNN partitioning for the collaboration between the cloud, the edge, and the mobile Web browser. Second, we propose a differentiated DNN computation scheduling approach specially designed for the edge platform. On one hand, performing part of DNN computations on mobile Web without decreasing the UX (i.e., keep response latency below a specific threshold) will effectively reduce the computing cost of the cloud system; on the other hand, performing the remaining DNN computations on the cloud (including remote and edge cloud) will also improve the inference latency and thus UX when compared to the self-contained solution. Obviously, our collaborative solution will balance the interests of both users and service providers. Experiments have been conducted in an actually deployed 5G trial network, and the results show the superiority of our proposed collaborative solution.
Giardia, 338 years after its discovery: The challenge ahead

Antony van Leeuwenhoek, the Dutch tradesman who first identified Giardia in 1681, has become a legend in Parasitology. Last November 4th marked the 338th anniversary of the submission of his letter, addressed to Sir Robert Hook, the then Secretary of the Royal Society of London, in which he described his observations in his own faecal sample: “[. ] I have looseness, at intervals of 2, 3 or 4 times a day. But this summer this befell me very often, and especially when I partook of hot smoked beef, that was a bit fat, or ham, which food I ́m very fond of; indeed, it persisted once for three days running, and whatever food I took, I kept in my body not much above 4 hours. My excrement being so thin, I was at divers times persuaded to examined it; and each time I kept in mind what food I had eaten, and what food I had drunk, and what found afterwards” [. ] “All the particles aforesaid lay in a clear transparent medium, wherein I have sometimes also seen animalcules a-moving very prettily; some of them a bit bigger, others a bit less, than a blood-globule, but all of one and the same make. Their bodies were somewhat longer than broad, and their belly, was flattish, furnished with sundry little paws, where with they made such a stir in the clear medium and among the globules, that you might even fancy you saw a woodlouse running up against a wall; and albeit they made a quick motion with their paws, yet for all that they made but slow progress” [1]. These observations were not only the first credited description of a protozoan, but also the first description of its clinical manifestations, even when van Leeuwenhoek did not associated any organism with his disease symptoms. Despite initial observations were followed by a long silence, during these 338 years, mainly the last 75 years, there have been many other key discoveries and notable developments in the history of Giardia, including the observations of Rendtorff on transmission [2] and the inclusion of 5-nitroimidazole (5-NIs) compounds into the antigiardial arsenal [3,4]. ISSN: 2637-4501
On structure and optimisation in computational harmonic analysis - The key aspects in sparse regularisation

Computational harmonic analysis has a rich history spanning more than half a century, where the last decade has been strongly inﬂuenced by sparse regularisation and compressed sensing. The theory has matured over the last years, and it has become apparent that the success of compressed sensing in ﬁelds like Magnetic Resonance Imaging (MRI), and imaging in general, is due to speciﬁc structures beyond just sparsity. Indeed, structured sampling and the structure of images represented in X-lets, for example sparsity in levels, are key ingredients. The ﬁeld relies on the crucial assumption that one can easily compute minimisers of convex optimisation problem. This assumption is false in general. One can typically easily compute the objective function of convex optimisation problems, but not minimisers. However, due to the speciﬁc features in compressed sensing, one can actually compute the desired minimisers fast and reliably to sufﬁcient precision. In short, as we demonstrate here: the success of sparse regularisation and compressed sensing is due to speciﬁc key structures that allow for a beneﬁcial interaction between harmonic analysis and optimisation.