Miracle-dz/UniFAR-FTUs huggingface dataset:
A Machine Learning Model for Predicting Mortality within 90 Days of Dialysis Initiation

Visual Abstract Key Points This paper presents an eXtreme Gradient Boosting (XGBoost) model that predicted mortality in the first 90 days after dialysis initiation using data from the United States Renal Data System. Such a model could facilitate patient-clinician shared decision making on whether to initiate dialysis or pursue medical management. The XGBoost models discriminated mortality risk in both the nonimputed (c=0.826) and imputed (c=0.827) models. Background The first 90 days after dialysis initiation are associated with high morbidity and mortality in end-stage kidney disease (ESKD) patients. A machine learning–based tool for predicting mortality could inform patient-clinician shared decision making on whether to initiate dialysis or pursue medical management. We used the eXtreme Gradient Boosting (XGBoost) algorithm to predict mortality in the first 90 days after dialysis initiation in a nationally representative population from the United States Renal Data System. Methods A cohort of adults initiating dialysis between 2008–2017 were studied for outcome of death within 90 days of dialysis initiation. The study dataset included 188 candidate predictors prognostic of early mortality that were known on or before the first day of dialysis and was partitioned into training (70%) and testing (30%) subsets. XGBoost modeling used a complete-case set and a dataset obtained from multiple imputation. Model performance was evaluated by c-statistics overall and stratified by subgroups of age, sex, race, and dialysis modality. Results The analysis included 1,150,195 patients with ESKD, of whom 86,083 (8%) died in the first 90 days after dialysis initiation. The XGBoost models discriminated mortality risk in the nonimputed (c=0.826, 95% CI, 0.823 to 0.828) and imputed (c=0.827, 95% CI, 0.823 to 0.827) models and performed well across nearly every subgroup (race, age, sex, and dialysis modality) evaluated (c>0.75). Across predicted risk thresholds of 10%–50%, higher risk thresholds showed declining sensitivity (0.69–0.04) with improving specificity (0.79–0.99); similarly, positive likelihood ratio was highest at the 40% threshold, whereas the negative likelihood ratio was lowest at the 10% threshold. After calibration using isotonic regression, the model accurately estimated the probability of mortality across all ranges of predicted risk. Conclusions The XGBoost-based model developed in this study discriminated risk of early mortality after dialysis initiation with excellent calibration and performed well across key subgroups.
Self-expansion motivation and inclusion of others in self: An updated review

In this paper we review the self-expansion model in the context of close relationships, focusing primarily on work in the last 20 years, considering throughout variation in our samples across cultures and other demographics—both in existing studies and in potential implications for future research. The self-expansion model has two key principles. The first half of the paper focuses on the motivational principle: The model theorizes that people have a fundamental desire to expand the self—that is, to increase their self-efficacy, perspectives, competence, and resources, and this often occurs through relationships in general. The second half of the paper focuses on the inclusion-of-other-in-the-self principle, in that a major means of self-expansion is through close relationships, when one’s partner’s identities, perspectives, skills, and resources become to some extent “included in the self” as also one’s own. For each principle we briefly describe its foundational research support and then explore the extensive, significant work of the last 20 years substantially expanding and deepening the implications of the model. The majority (although with some interesting exceptions) of studies have fallen short of testing the universal breadth of the model. As we review the research, we consider where the studies were conducted and with what kinds of populations. Where there are data from diverse populations, the overall pattern of results are generally similar. However, there were individual differences found within the populations studied, such as in attachment style, that affected the operation of both principles. Since there are well known differences in the distribution of such individual differences across populations of many types, it is quite likely that while the basic patterns may not differ, future research will show different degrees of operation in different populations.
Spatial uncertainty in herbarium data: simulated displacement but not error distance alters estimates of phenological sensitivity to climate in a widespread California wildflower

Herbarium records provide a broad spatial and temporal range with which to investigate plant responses to environmental change. Research on plant phenology and its sensitivity to climate has advanced with the increasing availability of digitized herbar-ium specimens, but limitations of specimen-derived data can undermine the inferences derived from such research. One issue that has received little attention is collection site uncertainty (i.e. error distance), a measure of confidence in the location from which a specimen was collected. We conducted comparative analyses of phenoclimatic models to determine whether spatial deviations of 2, 5, 15 or 25 km between recorded and simulated collection sites, as well as the error distance reported in digitized records, affect estimates of the phenological sensitivity of flowering time to annual temperature and precipitation in a widespread annual California wildflower. In this approach, we considered both spatial and interannual variation in climatic conditions. Simulated site displacements led to increasingly weak estimates of phenological sensitivity to temperature and precipitation anomalies with increasing distances. However, we found no significant effect of reported error distance magnitude on estimates of phenological sensitivity to climate normals or anomalies. These findings suggest that the spatial uncertainty of collection sites among specimens of widely collected plant species may not adversely affect estimates of phenological sensitivity to climate, even though real discrepancies and georeferencing inaccuracy can negatively impact such estimates. Collection site uncertainty merits further attention as a potential source of noise in herbarium data, especially for research on how plant traits respond to spatial and inter-annual climatic variation.
The Role of Organizational Culture in Moderating Corporate Governance Practice Influence on Faith-Based Hospitals Performance in Kenya

In Kenya, faith-based hospitals provide 40% health care services to the me-dium and low-income populations in the rural areas. These hospitals are fac-ing sustainability challenges because of poor organizational performance. These failures have been attributed to overlooking the adoption of corporate governance practices where for instance boards of management of health facilities are largely made up of religious officials, therefore making the facilities lack proper corporate culture when compared to their more privately owned health facilities counterparts. It is against this background that this study sought to examine the influence of corporate governance on hospitals overall and the moderating effect of corporate culture on the influence. A hospital based census with mixed data collection method was employed. For quantitative data, questionnaires were used with senior managers of Christian faith-based hospitals Key Informant Interviews with 9 purposively sampled informants: 2 from CHAK secretariat, 2 from KCCB secretariat and 5 board chairpersons of governing boards in purposively selected level 5 faiths based hospital. For quantitative data, descriptive and inferential analysis techniques were used while for qualitative data, content analysis was done. From the regression results, corporate governance practices of board composition, accountability, stewardship of resources and shared strategic direction had significant and positive influences on the performance of faith-based hospitals in Kenya. The study recommends that proprietors ensure that the criteria for choosing their board members are enhanced and improved to ensure there is no bias in the selection process and that boards intentionally and actively in-volve all stakeholders in the decision-making process of the organization, management should ensure accountability aspects and the related policies are adhered to, board members should be properly inducted and continuously trained on governance to ensure they execute their mandate effectively.
A 325F2 Physical Unclonable Function Based on Contact Failure Probability With Bit Error Rate < 0.43 ppm After Preselection With 0.0177% Discard Ratio

Preselection methods in which unstable bitcells are discarded are widely used to enhance the stability of the physical unclonable function (PUF). If the discard range of the preselection is too narrow, all unstable bitcells cannot be discarded, whereas, if the discard range is too wide, the PUF circuit area increases because the number of redundant bitcells should increase. Moreover, the discard range of most previous PUFs is not determined by theoretical analysis but rather by repeated measurements, which requires a long test time and cannot determine the accurate discard range to guarantee the PUF stability. This article demonstrates an efficient preselection method to determine the discard range through a theoretical analysis of the PUF entropy source for the PUF based on contact failure probability (contact PUF). After this preselection with the discard ratio of 0.0177%, no PUF responses changed among 2367040 bits from 1138 chips, i.e., bit error rate < 0.43 ppm, in seven harsh environmental tests regulated by the Joint Electron Device Engineering Council (JEDEC) standard. The proposed preselection method also enables the contact PUF to be implemented in a small area due to the low discard ratio. A small-area design methodology of contact PUF bitcells is also proposed. The PUF bitcell area per bit is $325F^{2}$ , the smallest area compared to previous PUFs. The contact PUF with the proposed preselection applied is fabricated in 100-nm CMOS technology. It achieves 0.4999 of uniqueness and 0.9942 of Shannon entropy and passes all applicable randomness tests stipulated by the National Institute of Standards and Technology (NIST) SP800-22.
The Early Permian assembly of the Jiamusi Massif and Khanka Massif: Evidence from sediment sources

The Jiamusi‐Khanka Massif is an important tectonic unit of the Central Asian Orogenic Belt in North‐east China. Its Late Palaeozoic tectonic properties and the timing of assembly have restricted the understanding of the tectonic evolution process at the eastern segment of the Central Asian Orogenic Belt for a long time. Based on the study of clastic rock petrology and zircon U–Pb chronology of the Early Permian Erlongshan Formation in Mishan, it is clear that the zircon age of the Early Permian Erlongshan Formation in Mishan is mainly Late Palaeozoic, with a major age peak at 300 ± 3 Ma and secondary age peaks at 356 ± 7 Ma and 475 ± 10 Ma. The provenance mainly comes from the magmatic arc source area, and Early Palaeozoic (500–420 Ma) detrital zircons mainly come from the south‐east margin of Jiamusi Massif, Late Palaeozoic (400–270 Ma) detrital zircons mainly come from the eastern margin of Jiamusi Massif and the northern margin of Khanka Massif. Among them, detrital zircons of a special age group 330–310 Ma come from the north of Khanka Massif, while 490–470 Ma detrital zircons which are common in the Early‐Middle Permian strata of Khanka Massif come from Jiamusi Massif. Combined with the evidence of petrology and palaeontology, this paper believes that the Early Permian Jiamusi Massif and Khanka Massif should be a unified Massif, that is, Jiamusi‐Khanka Massif.
Neural Reranking-Based Collaborative Filtering by Leveraging Listwise Relative Ranking Information

Reranking is a critical task used to refine the initial collaborative filtering (CF) recommendation by incorporating information from different viewpoints, such as the extra item side-information and user profile. In this article, a neural reranking-based CF (NRCF) model is proposed to leverage composite viewpoints from the basic CF model and user preference. More precisely, the predictive implicit user preference is first constructed from the initial top- $k$ items. The implicit user preference is then aggregated with the explicit user embedding to enrich the user intent representation. Moreover, the traditional listwise loss functions for reranking optimization are suboptimal, due to the fact that they neglect the relative ranking information (ReinRank) between the unobserved and positive items. To address this issue, a novel listwise loss function that leverages relative ranking information, referred to as ReinRank, is proposed for reranking optimization. ReinRank assigns different values to the unobserved items, according to their relative ranking distances between the positive items. Extensive experiments are performed on three public benchmarks and different CF models, in order to demonstrate the effectiveness of NRCF and ReinRank.
Pengaruh Struktur Aset dan Likuiditas terhadap Struktur Modal dengan Ukuran Perusahaan sebagai Variabel Moderasi

Penelitian ini bertujuan untuk menguji pengaruh dari struktur aset serta likuiditas terhadap struktur modal menggunakan ukuran perusahaan sebagai variabel moderasi. Model yang digunakan pada penelitian berupa desain penelitian kausalitas dengan jenis data kuantitatif atau data sekunder. Populasi dalam penelitian ini mempergunakan perusahaan property dan real estate yang terdaftar di Bursa Efek Indonesia pada tahun 2015-2019. Proses pemilihan sampel melalui metode purposive sampling, sehingga diperoleh sejumlah 100 data observasi dari 20 perusahaan yang terpilih sebagai sampel. Pengujian hipotesis dilakukan memakai model analisis regresi linier berganda serta uji moderated regression analysis (MRA) untuk menguji variabel moderator. Hasil dari penelitian didapatkan bahwa struktur aset dan likuiditas berpengaruh secara simultan terhadap struktur modal. Kemudian, secara parsial struktur aset memiliki pengaruh positif terhadap struktur modal, sedangkan likuiditas secara parsial berpengaruh negatif terhadap struktur modal. Selanjutnya ukuran perusahaan sebagai moderasi tidak mampu memoderasi pengaruh struktur aset terhadap struktur modal, namun mampu memoderasi pengaruh likuiditas terhadap struktur modal.
Study on Tourism Consumer Behavior and Countermeasures Based on Big Data

In our study, through consulting, summarizing, and analyzing a large number of related literature studies on tourism consumer behavior, tourism big data, text data analysis, and so on, a framework of research ideas on tourism consumption was constructed. The train browser, NLPIR, and other software packages are used to crawl, preprocess, and mine the travel sample data, and the word frequency analysis, co-occurrence analysis, content analysis, sentiment analysis, network analysis, and other methods are used to analyze the characteristics and decision-making behavior of tourists. Based on the results of behavioral analysis, we proposed tourism development strategies from three aspects: reforming and promoting tourism marketing strategies, improving tourism product and service quality, and improving tourism destination management methods. The results show that (1) for the tourist characteristics, taking into account the factors of climate and geographical location, the domestic market is divided into four grades of markets, and different marketing strategies are adopted according to different market characteristics; (2) for the tourism decision-making behavior, a “push-pull resistance” tourism decision-making model was established through word frequency analysis, co-occurrence analysis, and content analysis; (3) for the tourism consumption preferences, through network analysis of scenic spots, it is found that there are three tourist routes preferred by tourists; and (4) for the tourism perception evaluation behavior, based on the “cognitive-emotional” model, this study describes the tourism image from the two dimensions of the cognitive image and emotional image. Generally speaking, tourists show a positive perception state. The research on tourism consumer behavior based on UGC (user-generated content) data can help scenic spots and other tourism companies to understand the characteristics and rules of tourists' behavior, understand the consumption preferences of different tourism groups, develop diversified tourism products, improve the quality of tourism services, and further cater to market segments. This research provides a new idea for tourist attractions and tourism management departments to monitor tourist behavior through big data analysis.
Interleukin-35 Prevents the Elevation of the M1/M2 Ratio of Macrophages in Experimental Type 1 Diabetes

Macrophages play an important role in the early development of type 1 diabetes (T1D). Based on the phenotype, macrophages can be classified into pro-inflammatory (M1) and anti-inflammatory (M2) macrophages. Despite intensive research in the field of macrophages and T1D, the kinetic response of M1/M2 ratio has not been studied in T1D. Thus, herein, we studied the M1 and M2 macrophages in the early development of T1D using the multiple low dose streptozotocin (MLDSTZ) mouse model. We determined the proportions of M1 and M2 macrophages in thymic glands, pancreatic lymph nodes and spleens on days 3, 7 and 10 after the first injection of STZ. In addition, we investigated the effect of IL-35 in vivo on the M1/M2 ratio and IL-35+ plasmacytoid dendritic cells in diabetic mice and in vitro on the sorted macrophages. Our results revealed that the M1/M2 ratio is higher in STZ-treated mice but this was lowered upon the treatment with IL-35. Furthermore, IL-35 treated mice had lower blood glucose levels and a higher proportion of IL-35+ cells among pDCs. Macrophages treated with IL-35 in vitro also had a higher proportion of M2 macrophages. Together, our data indicate that, under diabetic conditions, pro-inflammatory macrophages increased, but IL-35 treatment decreased the pro-inflammatory macrophages and increased anti-inflammatory macrophages, further suggesting that IL-35 prevents hyperglycemia by maintaining the anti-inflammatory phenotype of macrophages and other immune cells. Thus, IL-35 should be further investigated for the treatment of T1D and other autoimmune disorders.
A Needs-based Evaluation of EAP Syllabuses

The main purpose of the present study was to analyze reading comprehension needs of undergraduate students and determine whether EAP syllabuses are developed based on these reading comprehension needs. The other purpose of the study was to see how EAP classes represent reading comprehension needs. To this end, 656 undergraduate students, 75 graduate students, 150 post-graduate students, 75 content teachers and 30 EAP teachers of 15 randomly selected academic disciplines filled in a reading comprehension needs analysis questionnaire. Open ended questions, classroom observation and content analysis of the syllabuses were also used to triangulate the data in terms of sources and methods. The findings indicated that reading comprehension needs were considered either ‘important’ or ‘very important’ by all participants. Significant differences were found in the perceptions of participants regarding the importance of sub-skills and strategies of reading comprehension needs such as skimming the text, knowledge of general vocabulary and knowledge of specialized terminologies. Classroom observations showed that EAP classes do not address undergraduate students’ reading comprehension needs but translate the texts and provide Persian meaning of general and specific words. More importantly, it was found that EAP syllabuses have not been fully developed based on reading comprehension needs of undergraduate students. The findings suggest that an eclectic multi-layered approach to syllabus design which takes into account content-based, task-based, text-based and genre-based approaches and critically considers voices of different EAP stakeholders should be considered in redesigning EAP syllabuses.
The Antibacterial and Cytotoxic Effects of Silver Nanoparticles Coated Titanium Implants: A Narrative Review

Nanotechnology has become an emerging research field with numerous biomedical scientific applications. Silver possesses bactericidal activities that have been harnessed for centuries; however, there is a concern about the toxic effects of silver nanoparticles. This paper aims to provide an overview of silver-treated dental implants and discuss their potential to reduce the prevalence of peri-implant diseases. An electronic search was performed using PubMed. After screening, data extraction was performed on the 45 remaining articles using inclusion and exclusion criteria. Most of the articles demonstrated that silver nanoparticles embedded in a coating layer and/or on surface-treated titanium exhibit sound antibacterial effects and biocompatibility. Most of the reviewed studies revealed that silver nanoparticles on dental implant surfaces reduced cytotoxicity but provided a prolonged antibacterial effect. The cytotoxicity and antibacterial effect are closely linked to how the silver nanoparticles are released from the titanium surfaces, where a slower release increases cell viability and proliferation. However, to improve the clinical translation, there is still a need for more studies, especially evaluating the long-term systemic effects and studies recreating the conditions in the oral cavity.
The Prevalence of Dizziness and Vertigo in COVID-19 Patients: A Systematic Review

Clinical manifestations of COVID-19 include symptoms of vertigo and dizziness, which is rather unsurprising, since SARS-CoV-2 neurotropism may inflict a broad spectrum of neuropathic effects. The widespread nature of central and peripheral audiovestibular pathways suggests that there may be several probable pathophysiological mechanisms. The cytokine storm, CNS infiltration of the virus through ACE 2 receptors, and other systemic factors can be responsible for the significant number of COVID-19 patients reported to experience symptoms of vertigo and dizziness. In this paper, we present a systematic review of clinical studies reporting the detection of dizziness and vertigo as clinical manifestations of COVID-19 and discuss their etiopathogenesis.