Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Complexity of Simulated Annealing

Simulated annealing is an effective and general means of optimization. It is in fact inspired by metallurgy, where the temperature of a material determines its behavior in thermodynamics. Likewise, in simulated annealing, the actions that the algorithm takes depend entirely on the value of a variable which captures the notion of temperature. Typically, simulated annealing starts with a high temperature, which makes the algorithm pretty unpredictable, and gradually cools the temperature down to become more stable. A key component that plays a crucial role in the performance of simulated annealing is the criteria under which the temperature changes namely, the cooling schedule. Motivated by this, we study the following question in this work: "Given enough samples to the instances of a specific class of optimization problems, can we design optimal (or approximately optimal) cooling schedules that minimize the runtime or maximize the success rate of the algorithm on average when the underlying problem is drawn uniformly at random from the same class? " We provide positive results both in terms of sample complexity and simulation complexity. For sample complexity, we show that $\tilde O(\sqrt{m})$ samples suffice to find an approximately optimal cooling schedule of length $m$. We complement this result by giving a lower bound of $\tilde \Omega(m^{1/3})$ on the sample complexity of any learning algorithm that provides an almost optimal cooling schedule. These results are general and rely on no assumption. For simulation complexity, however, we make additional assumptions to measure the success rate of an algorithm. To this end, we introduce the monotone stationary graph that models the performance of simulated annealing. Based on this model, we present polynomial time algorithms with provable guarantees for the learning problem.
Sociodemographic Characteristic and Health Related Quality of Life in Outpatients of Type 2 Diabetes Mellitus Under JKN

: The aim of study was carried out to determine differences of health related qualitiy of life (HRQoL) with sociodemographic characteristic in type 2 diabetes mellitus outpatiens at one of government hospital in Jakarta. It was a cross-sectional study conducted from February to April 2015. Total of samples were 83 patients. Male 31(37.4%) and female 52(62.6%). HRQoL associated with level education was difference significantly (P<0.05). Based on score of domain quality of life, female had higher score (69.82 ± 3.14) of frequency of symptoms domain than male (67.32 ± 4.50) (P<0.05). The oldest patients had the highest score (P<0.05) in domain of satisfaction. In contrast, the oldest patients had the the most decrease score (64.14 ± 4.03) in domain of frequency of symptoms (P<0.05). Patients of senior high school had lower score (60.17 ± 24.65) in domain of treatmant satisfaction than patients of diploma/ bachelor (78.78 ± 21.98). Score of domain of frequency of symptoms was higher on patients employed than none (P<0.05). The household income did not influence all domain (P>0.05). Furthermore, diabetes duration affected both domain of satisfaction (P=0.005) and frequency of symptoms (P=0.00). In conclusion, only education level of characteristic sociodemographic had difference significantly to HRQoL among type 2 diabetes mellitus outpatients.
CURL: Neural Curve Layers for Global Image Enhancement

We present a novel approach to adjust global image properties such as colour, saturation, and luminance using human-interpretable image enhancement curves, inspired by the Photoshop curves tool. Our method, dubbed neural CURve Layers (CURL), is designed as a multi-colour space neural retouching block trained jointly in three different colour spaces (HSV, CIELab, RGB) guided by a novel multi-colour space loss. The curves are fully differentiable and are trained end-to-end for different computer vision problems including photo enhancement (RGB-to-RGB) and as part of the image signal processing pipeline for image formation (RAW-to-RGB). To demonstrate the effectiveness of CURL we combine this global image transformation block with a pixel-level (local) image multi-scale encoder-decoder backbone network. In an extensive experimental evaluation we show that CURL produces state-of-the-art image quality versus recently proposed deep learning approaches in both objective and perceptual metrics, setting new state-of-the-art performance on multiple public datasets. Our code is publicly available at: https://github.com/sjmoran/CURL.
Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis

Lung adenocarcinoma is the most frequently diagnosed subtype of nonsmall cell lung cancer. The molecular mechanisms of the initiation and progression of lung adenocarcinoma remain to be further determined. This study aimed to screen genes related to the progression of lung adenocarcinoma. By weighted gene coexpression network analysis (WGCNA), we constructed a free-scale gene coexpression network to evaluate the correlations between multiple gene sets and patients' clinical traits, then further identify predictive biomarkers. GSE11969 was obtained from the Gene Expression Omnibus (GEO) database which contained the gene expression data of 90 lung adenocarcinoma patients. Data of the Cancer Genome Atlas (TCGA) were employed as the validation cohort. After the average linkage hierarchical clustering, a total of 9 modules were generated. In the clinical significant module (R = 0.44, P < 0.0001), we identified 29 network hub genes. Subsequent verification in the TCGA database showed that 11 hub genes (ANLN, CDCA5, FLJ21924, LMNB1, MAD2L1, RACGAP1, RFC4, SNRPD1, TOP2A, TTK, and ZWINT) were significantly associated with poor survival data of lung adenocarcinomas. Besides, the results of receiver operating characteristic curves indicated that the mRNA levels of this group of genes exhibited high specificity and sensitivity to distinguish malignant lesions from nonmalignant tissues. Apart from mRNA levels, we found that the protein abundances of these 11 genes were remarkably upregulated in lung adenocarcinomas compared with normal tissues. In conclusion, by the WGCNA method, a panel of 11 genes were identified as predictive biomarkers for tumorigenesis and poor prognosis of lung adenocarcinomas.
An algorithm for reconstruction of triangle-free linear dynamic networks with verification of correctness

Reconstructing a network of dynamic systems from observational data is an active area of research. Many approaches guarantee a consistent reconstruction under the relatively strong assumption that the network dynamics is governed by strictly causal transfer functions. However, in many practical scenarios, strictly causal models are not adequate to describe the system and it is necessary to consider models with dynamics that include direct feedthrough terms. In presence of direct feedthroughs, guaranteeing a consistent reconstruction is a more challenging task. Indeed, under no additional assumptions on the network, we prove that, even in the limit of infinite data, any reconstruction method is susceptible to inferring edges that do not exist in the true network (false positives) or not detecting edges that are present in the network (false negative). However, for a class of triangle-free networks introduced in this article, some consistency guarantees can be provided. We present a method that either exactly recovers the topology of a triangle-free network certifying its correctness or outputs a graph that is sparser than the topology of the actual network, specifying that such a graph has no false positives, but there are false negatives.
A Capacity-achieving One-message Key Agreement With Finite Blocklength Analysis.

Information-theoretic secret key agreement (SKA) protocols are a fundamental cryptographic primitive that are used to establish a shared secret key between two or more parties. In a two-party SKA in source model, Alice and Bob have samples of two correlated variables, that are partially leaked to Eve, and their goal is to establish a shared secret key by communicating over a reliable public channel. Eve must have no information about the established key. In this paper, we study the problem of one-message secret key agreement where the key is established by Alice sending a single message to Bob. We propose a one-message SKA (OM-SKA) protocol, prove that it achieves the one-way secret key capacity, and derive finite blocklength approximations of the achievable secret key length. We compare our results with existing OM-SKAs and show the protocol has a unique combination of desirable properties.
Distributional Semantic Modeling: a Revised Technique to Train Term/Word Vector Space Models Applying the Ontology-related Approach

We design a new technique for the distributional semantic modeling with a neural network-based approach to learn distributed term representations (or term embeddings) – term vector space models as a result, inspired by the recent ontology-related approach (using different types of contextual knowledge such as syntactic knowledge, terminological knowledge, semantic knowledge, etc.) to the identification of terms (term extraction) and relations between them (relation extraction) called semantic pre-processing technology – SPT. Our method relies on automatic term extraction from the natural language texts and subsequent formation of the problem-oriented or application-oriented (also deeply annotated) text corpora where the fundamental entity is the term (includes non-compositional and compositional terms). This gives us an opportunity to changeover from distributed word representations (or word embeddings) to distributed term representations (or term embeddings). The main practical result of our work is the development kit (set of toolkits represented as web service APIs and web application), which provides all necessary routines for the basic linguistic pre-processing and the semantic pre-processing of the natural language texts in Ukrainian for future training of term vector space models.
Laxative Effects of Yangyin Tongmi Capsule on a Model of Diphenoxylate-Induced Constipation in Mice

Constipation is characterized by reduced number of bowel movements, dry stools, and difficult defecation. Yangyin Tongmi capsule (YTC), a traditional Chinese formula, is used in the treatment of constipation, while the underlying mechanisms remain unknown. Herein, this work attempted to prove the effects of YTC on constipation treatment and its possible mechanisms. KM mice were randomly divided into four groups (n = 10/group) and treated with double distilled water (Control), diphenoxylate (Model: 10 mg/kg), or diphenoxylate plus low-dose YTC (L-YTC: 0.6 g/kg) or high-dose YTC (H-YTC: 1.2 g/kg). The data indicated that YTC can significantly shorten the discharge time of the first black stool, improve intestinal propulsion rate, and increase the water content and quantity of feces in mice. ELISA suggested that YTC regulate the content of intestinal hormones and neurotransmitters, such as motilin (MTL), gastrin (GT), somatostatin (SST), substance P (SP), acetylcholine (Ach), and nitric oxide (NO). The expression levels of aquaporin 3 (AQP3) and aquaporin 8 (AQP8) in the colon were examined by immunohistochemistry. In the meantime, the expression levels of P2X2, C-kit, and stem cell factor (SCF) in the colon were examined by western blot analysis. The results of this study suggest that YTC has mitigative effects on diphenoxylate-induced constipation by regulating the content of intestinal hormones and neurotransmitters and regulating the expression of related proteins in the colon.
Substance Use among 12th Grade Aged Youths by Dropout Status

X The pattern of higher use rates among dropouts than those still in school generally held for both males and females, as well as for whites and blacks; however, Hispanic 12th grade aged dropouts and those still in school had similar past month rates of alcohol and illicit drug use In the United States, about 75 percent of youths who enter public high school as freshmen eventually graduate from high school in 4 years (or average freshman graduation rate). 1 This is an important public health issue because, in general, adults who do not graduate from high school tend to have lower paying jobs than those who do and thus are at greater risk for living in poverty, lacking health insurance, and suffering from poor health.2,3,4 Moreover, high school dropouts typically have higher rates of substance use than high school graduates.5
Chrysophyllum cainito: A Tropical Fruit with Multiple Health Benefits

Chrysophyllum cainito is a tropical fruit tree with multiple benefits to human health. C. cainito possesses strong antioxidant properties either in vitro or in vivo. Extracts from the leaves, stem bark, fruits, peel, pulp, or seed of C. cainito are promising candidates in traditional medicine for curing diabetes and fighting against bacterial, fungal, and viral infections. C. cainito leaf extract alone or in a complex formula exhibits anti-inflammatory responses by reducing hypersensitivity, acts as inflammatory markers, and has antinociceptive effects. The leaf extract also increases wound healing speed and assists in regulating fat uptake. In addition, the C. cainito fruit shows anticancer activity against osteosarcoma. In conclusion, the aerial parts of C. cainito have strong beneficial biological effects on human health.
MicroRNA-200a Promotes Phagocytosis of Macrophages and Suppresses Cell Proliferation, Migration, and Invasion in Nasopharyngeal Carcinoma by Targeting CD47

Nasopharyngeal carcinoma (NPC) causes severe oncogenic lesions in the nasopharynx. CD47, a transmembrane integrin-associated protein, plays a key role in the ability of tumor cells to escape phagocytosis, working as an immune checkpoint in the immune response. Besides this role, CD47 has been reported to regulate cell proliferation and migration. The present study addresses the relationship between CD47 and microRNA-200a and examines their regulatory mechanisms in NPC. Bioinformatics analyses and dual-luciferase reporter assays were used to confirm the putative relationship between miR-200a and CD47, and their interaction was further detected using western blotting and RT-PCR. Further, results showed that miR-200a affect NPC cell proliferation, migration, and invasion by regulating CD47. A cell phagocytosis assay showed that miR-200a and a CD47 monoclonal antibody increased the sensitivity of NPC cells to macrophage phagocytosis by inhibiting the functions of CD47. Additionally, miR-200a expression was suppressed and CD47 expression increased in both clinical NPC tissues and cell lines. Taken together, these results show the miR-200a/CD47 combination as a potential therapeutic for treatment of NPC.
Bushen Tiaojing (II and III) Decoctions Activate MAPK14 and MAPK3/1 to Promote the Expression of Cumulus Expansion-Related Factors in Mice

Background Bushen Tiaojing Decoctions (BSTJ-II-D and BSTJ-III-D) are used to assist pregnancy in clinical practice. In this study, we explored the ability of sequential administration of BSTJ-II-D and BSTJ-III-D to promote cumulus cell (CC) expansion and its underlying mechanisms in controlled ovarian hyperstimulation (COH) mice. Methods Kunming mice were randomly divided into three groups. The normal group was injected intraperitoneally with saline, and distilled water was administered orally by gavage. As the COH model, mice were injected with GnRHa, eCG, and hCG. Subsequently, the BSTJD group received BSTJ-II-D and BSTJ-III-D orally by gavage, while the control group received distilled water. We evaluated CC expansion and oocyte first polar body (PB1) extrusion under a stereomicroscope. Serum levels of follicle-stimulating hormone (FSH) were detected by radioimmunoassay. The expression of the CC expansion-related factors PTX3 and PTGS2 was detected by immunofluorescence, western blot, and quantitative real-time-polymerase chain reaction analyses (qRT-PCR). Expression of p-MAPK14, p-MAPK3/1, MAPK14, and MAPK3/1 was detected by western blot analysis. Results Sequential administration of BSTJ-II-D and BSTJ-III-D promoted cumulus expansion and oocyte PB1 extrusion and upregulated PTX3 and PTGS2 expression at the mRNA and protein levels. Furthermore, the levels of p-MAPK14/MAPK14, p-MAPK3/1/MAPK3/1 proteins, and serum FSH in the BSTJD group were higher than those in the normal and control groups. Conclusions Sequential administration of BSTJ-II-D and BSTJ-III-D promotes cumulus expansion and oocyte maturation in COH mice by increasing FSH expression and activating the MAPK14 and MAPK3/1 signalling pathways, thereby increasing expression of PTX3 and PTGS2.
Composite Fading Models Based on Inverse Gamma Shadowing: Theory and Validation

We introduce a general approach to characterize composite fading models based on inverse gamma (IG) shadowing. We first determine to what extent the IG distribution is an adequate choice for modeling shadow fading, by means of a comprehensive test with field measurements and other distributions conventionally used for this purpose. Then, we prove that the probability density function and cumulative distribution function of any IG-based composite fading model are directly expressed in terms of a Laplace-domain statistic of the underlying fast fading model and, in some relevant cases, as a mixture of well-known state-of-the-art distributions. Also, exact and asymptotic expressions for the outage probability are provided, which are valid for any choice of baseline fading distribution. Finally, we exemplify our approach by presenting several application examples for IG-based composite fading models, for which their statistical characterization is directly obtained in a simple form.
Advanced radiation therapies for meningioma

Radiotherapy has been used to treat meningiomas for decades, both in the primary setting when resection is not possible and as an adjunct to surgery in recurrent/ high grade disease. Newer radiotherapy planning and delivery techniques aim to optimise tumour control and minimise long-term toxicities. The purpose of this thesis was to explore the feasibility and potential for the use of advanced radiation planning and delivery techniques to treat meningiomas. In a prospective observational study of intensity modulated radiotherapy (IMRT) in fifty patients I demonstrated that IMRT is feasible and provided excellent dosimetric parameters. Medium term meningioma control rates were >90% in benign disease. Objective measures of toxicity were low. Visual symptoms improved in 38.5% of patients. In a pilot study of ten patients I showed that simultaneous 68Ga DOTATATE PET/MRI can be utilised in meningioma radiotherapy planning. Baseline levels of interobserver variability in target volume definition between three Observers using CT/MRI alone were very high (mean target volume conformity levels of 0.31-0.34). Levels of agreement improved only 4-5% with the addition of PET and there was negligible difference in contouring between standard PET(CT) and simultaneous PET(MRI). In a planning study of ten meningiomas I did not find a notable advantage for proton therapy (non-intensity modulated) over IMRT. The high quality of the IMRT plans left little room for improvement and range uncertainty restricted exploitation of proton dose deposition characteristics. In my review of the first six patients treated with the radionuclide 177Lutetium DOTATATE for advanced progressive meningioma, tumour growth rates were found to slow, but there was generally disease progression during treatment. In conclusion, advanced radiation techniques for meningioma treatment are feasible and can confer clinical benefit. However, advances in technology do not necessarily translate into therapeutic gains. Careful prospective evaluation is required to ensure their optimal use.
Methionine abrogates the renoprotective effect of a low-protein diet against diabetic kidney disease in obese rats with type 2 diabetes

Dietary interventions, including a low-protein diet (LPD) and methionine (Met) restriction, have shown longevity, anti-aging and metabolic health effects. We previously reported that the LPD has a renoprotective effect against diabetic kidney disease (DKD) in rats with type 2 diabetes and obesity. However, it is unclear whether the beneficial effect of the LPD is mediated by low-Met intake or how Met is related to the pathogenesis for DKD. We herein show that the addition of Met with the LPD abrogates the beneficial effects induced by the LPD such as anti-oxidative stress, anti-inflammation and anti-fibrosis, in diabetic kidney. Additionally, the increased levels of S-adenosylmethionine (SAM) in renal tubular cells, which are associated with the reduced expression of glycine N-methyltransferase (Gnmt) and non-restricted Met intake, contributes to the activation of mechanistic target of rapamycin complex 1 (mTORC1) and impaired autophagy, in diabetic kidney. Moreover, starvation-induced autophagy was suppressed in renal cortex of Gnmt null mice and amino acid free-induced autophagy was also suppressed by administration of SAM in cultured HK-2 cells. A LPD could exert a renoprotective effect through the suppression of mTORC1 and restoration of autophagy, which is associated with reduced levels of SAM due to low-Met intake, in diabetic kidney.
RIASEC Interests and the Big Five Personality Traits Matter for Life Success-But Do They Already Matter for Educational Track Choices?

OBJECTIVE Educational track choices have far-reaching consequences because they are associated with long-term life success. Theoretical approaches and previous empirical research have nearly exclusively identified family background and achievement as determinants of these choices. Although students' educational track choices might fit their personality, individual differences in personality have not been explored. We investigated the effects of two personality aspects-RIASEC interests and Big Five traits-on hierarchically ranked track choices (vocational vs. general educational track), alongside family background and achievement. METHOD We used two German data sets (TOSCA 10 study: N = 473; TOSCA study: N = 4,218) focusing on choices between the general educational track (leading to higher educational attainment) and the vocational track (leading to work life) at two different stages in educational careers. We ran several multiple (logistic) regressions. RESULTS The results showed that certain aspects of students' personality matter for educational track choices. Accordingly, across both studies, students with high Investigative or Enterprising interests more often chose the general educational track, whereas students high on Social or Conventional interests more often chose the vocational track-after the Big Five personality traits, achievement, and family background were controlled for. The Big Five traits showed no or only small significant associations with educational track choices. CONCLUSION These findings underscore the importance of considering individual differences when investigating important life outcomes such as track choices.