Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting metal uptake by wetland plants under aerobic and anaerobic conditions

Metal pollution can be a serious threat to ecosystems at a global scale. Although the bioavailability of potentially toxic metals is determined by many biotic and abiotic factors, including pH and redox potential, total metal concentrations in the soil are used widely to assess or predict toxicity. In the present study we tested the effect of desiccation of soils differing in acidification potential and total heavy metal contamination on the growth and metal uptake of three typical, common wetland species: Caltha palustris, Juncus effusus, and Rumex hydrolapathum. We found that plant growth in wet soils mainly was determined by nutrient availability, though in dry soils the combined effects of acidification and increased metal availability prevailed. Metal uptake under anaerobic conditions was best predicted by the acidification potential (sediment S/[Ca + Mg] ratio), not by total metal concentrations. We propose that this is related to radial oxygen loss by wetland plant roots, which leads to acidification of the rhizosphere. Under aerobic conditions, plant metal uptake was best predicted by the amount of CaCl2‐extractable metals. We conclude that total metal concentrations are not suitable for predicting bioavailability and that the above diagnostic parameters will provide insight into biogeochemical processes involved in toxicity assessment and soil policy.
Feedback stabilization over signal-to-noise ratio constrained channels

There has recently been significant interest in feedback stabilization problems over communication channels, including several with bit rate limited feedback. Motivated by considering one source of such bit rate limits, we study the problem of stabilization over a signal-to-noise ratio (SNR) constrained channel. We discuss both continuous and discrete time cases, and show that for either state feedback, or for output feedback delay-free, minimum phase plants, there are limitations on the ability to stabilize an unstable plant over an SNR constrained channel. These limitations in fact match precisely those that might have been inferred by considering the associated ideal Shannon capacity bit rate over the same channel.
Prediksi Volatilitas Indeks Harga Saham Gabungan Menggunakan GARCH

This study aims to determine the Volatility Prediction of the Indonesia Composite Index using GARCH. GARCH is a model for generating forecasts based on historical data using a function of its own past lag plus past innovations. This study uses quantitative methods. The data in this study are JKSE data for 11 (eleven) years, from 01-01-2012 to 31-12-2022. The volatility prediction is carried out for a year, namely in 2022. The results of this study indicate that the prediction accuracy is quite good with a MAPE of 17.26 percent. It was also found that volatility was quite pronounced, which rose significantly in May 2022 due to the effect of the absence of restrictions on the Eid holiday and decreased significantly in July 2022 due to the government extending the implementation of restrictions on community activities (PPKM) throughout Indonesia and dropping even more sharply due to the government increasing prices of Pertalite in September 2022.
Isolating the Effects of Body Mass and Energy Balance on Sleep and Metabolic Health

Obesity is associated with numerous metabolic and behavioral abnormalities, including excessive daytime sleepiness independent of sleep disorders (e.g., sleep apnea). In humans, obesity is traditionally classified by weight metrics such as body mass index (BMI); over one-third of Americans are obese based on BMI. The most common cause of obesity is chronic positive energy balance due to overconsumption of caloricallydense diets. However, it is difficult to isolate the independent effects of ‘overnutrition/positive energy balance’ and ‘excess body weight’ on metabolic and behavioral parameters since the former causes the latter. Therefore, the focus of this dissertation is to discover how diet/energy balance, independent from body weight, affect sleep/wake behavior and metabolic health using the high-fat diet (HFD)-induced obese mouse model. In Chapter 2, I introduce the Diet Switch (DS) feeding paradigm which generates two groups of mice of similar body weight by divergent energy balance. Using the DS protocol, I show that diet-induced changes to energy balance can affect sleep and wakefulness independent of actual body weight. In Chapter 3, I explore the role of a central regulator of energy balance, peroxisome proliferator-activated receptor gamma (PPARg), on HFDinduced sleep abnormalities; our results indicate that central PPARg does not influence sleep/wake behavior. In Chapter 4, I again use the DS feeding paradigm, but instead measure various molecular (blood biomarkers and hypothalamic gene expression), behavioral (spontaneous activity), and metabolic (indirect calorimetry) outcomes. Using linear regression modeling, I quantify the relative influence of body weight and diet/energy balance on these parameters, and relate these key findings to the results from Chapter 2. Taken together, these studies offer novel insights into the pathogenesis and reversibility of obesity-related sleep and metabolic disorders. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Neuroscience First Advisor Sigrid C. Veasey Second Advisor Allan I. Pack
Energy Efficient Resource Allocation for Multiuser Relay Networks

In this paper, a novel resource allocation algorithm is investigated to maximize the energy efficiency (EE) in multiuser decode-and-forward (DF) relay interference networks. The EE optimization problem is formulated as the ratio of the spectrum efficiency (SE) over the entire power consumption of the network subject to total transmit power, subcarrier pairing, and allocation constraints. The formulated problem is a nonconvex fractional mixed binary integer programming problem, i.e., NP-hard to solve. Furthermore, we resolve the convexity of the problem by a series of convex transformations and propose an iterative EE maximization algorithm to jointly determine the optimal subcarrier pairing at the relay, subcarrier allocation to each user pair and power allocation to all source and the relay nodes. Additionally, we derive an asymptotically optimal solution by using the dual decomposition method. To gain more insights into the obtained solutions, we further analyze the resource allocation algorithm in a two-user case with interference-dominated and noise-dominated regimes. In addition, a suboptimal algorithm is investigated with reduced complexity at the cost of acceptable performance degradation. Simulation results are used to evaluate the performance of the proposed algorithms and demonstrate the impacts of various network parameters on the attainable EE and SE.
Prediction of Human Elbow Torque from EMG Using SVM Based on AWR Information Acquisition Platform

In this paper a novel prediction method of elbow torque from EMG signal using SVM is proposed. How to model the relations between EMG signals and various kinematical aspects of the movement behavior is a difficult problem in the researches of neurophysiology and biomechanics. Traditional prediction methods include using neural networks to model the relations. However, these methods suffer from several problems, such as local minima, the difficulty of the selection of the model, etc. To address these problems, support vector machine is adopted to construct the nonlinear model. The efficiency of our proposed method is proved by experiment results.
Identifying primary and recurrent cancers using a SAS-based natural language processing algorithm

Objective Significant limitations exist in the timely and complete identification of primary and recurrent cancers for clinical and epidemiologic research. A SAS-based coding, extraction, and nomenclature tool (SCENT) was developed to address this problem. Materials and methods SCENT employs hierarchical classification rules to identify and extract information from electronic pathology reports. Reports are analyzed and coded using a dictionary of clinical concepts and associated SNOMED codes. To assess the accuracy of SCENT, validation was conducted using manual review of pathology reports from a random sample of 400 breast and 400 prostate cancer patients diagnosed at Kaiser Permanente Southern California. Trained abstractors classified the malignancy status of each report. Results Classifications of SCENT were highly concordant with those of abstractors, achieving κ of 0.96 and 0.95 in the breast and prostate cancer groups, respectively. SCENT identified 51 of 54 new primary and 60 of 61 recurrent cancer cases across both groups, with only three false positives in 792 true benign cases. Measures of sensitivity, specificity, positive predictive value, and negative predictive value exceeded 94% in both cancer groups. Discussion Favorable validation results suggest that SCENT can be used to identify, extract, and code information from pathology report text. Consequently, SCENT has wide applicability in research and clinical care. Further assessment will be needed to validate performance with other clinical text sources, particularly those with greater linguistic variability. Conclusion SCENT is proof of concept for SAS-based natural language processing applications that can be easily shared between institutions and used to support clinical and epidemiologic research.
An mHealth Intervention Strategy for Physical Activity Coaching in Cancer Survivors

Many cancer survivors experience severe fatigue long after they have finished curative treatment. The aim of this study was to develop an intervention strategy that aims to decrease cancer-related fatigue by integrating a physical activity coaching system in primary care physiotherapy. This development started from the current state of the art. Therefore, firstly, an overview is given about physical activity goals for cancer-related fatigue, relevant cognitive behavioral change factors in this context, and recommendations for using mobile Health applications. Subsequently, interviews with five experienced health professionals were held to define recommendations for the first draft intervention strategy. Via an iterative process with two physiotherapists and a patient, the final intervention strategy was developed. The final result is a 9-week intervention strategy that could benefit a large variety of patients with chronic cancer-related fatigue, that has the potential to be integrated successfully in current primary health care, and is currently evaluated in a large randomized controlled trial.
QTL-based association analyses reveal novel genes influencing pleiotropy of Metabolic Syndrome (MetS)

Objective: Metabolic Syndrome (MetS) is a phenotype cluster predisposing to type 2 diabetes and cardiovascular disease. We conducted a study to elucidate the genetic basis underlying linkage signals for multiple representative traits of MetS that we had previously identified at two significant QTLs on chromosomes 3q27 and 17p12.
Gender classification using ANN based on human radiation frequencies

This paper discusses about classification of human gender based on human frequencies of chakra points and brain regions. The main techniques used in this study are Artificial Neural Network (ANN) and k-fold cross-validation. ANN technique has been used for gender prediction and k-fold cross-validation for validation of classifier. All measurements are based on radio frequency readings. Data from 34 samples consist of 17 males and 17 females have been recorded. Three groups of points have been analyzed during classification and validation. Group 1 consists of seven chakra points and four brain regions, Group 2 consists of three chakra points and Group 3 consists of three chakra points and one brain region. The results show the variables in Group 1 are best for gender classification.
Intellectual Capital and Financial Performance of Quoted Manufacturing Firms

Purpose: This study examined the effect of intellectual capital on the financial performance of quoted manufacturing firms on the Nigerian Stock Exchange (NSE). The study specifically evaluated the effect of the value-added intellectual coefficient (VAIC) on Asset Turnover (ATR), Gross Profit Margin (GPM) and Return on Assets (ROA) from 2011 to 2019. Research Methodology: The research design used in the study is ex post facto. Non-probability sampling was the method of sampling that was employed in the investigation. Twenty (20) consumer products manufacturing companies that had been listed on the NSE for nine years made up the final sample. In earlier investigations, this was deemed sufficient for regression analysis. The analysis makes use of secondary data taken from the companies’ annual reports. The information spanned a nine-year span, from 2011 to 2019. Result: There is a non-significant negative effect of value added intellectual coefficient on the Asset Turnover Rate (ATR) of quoted manufacturing firms; however, there is a non-significant positive effect of VAIC on Gross Profit Margin (GPM) and Return on Assets (ROA) of quoted manufacturing firms. Limitation: The main limitation is the duration of time the study was conducted and the delisting of some firms during the period. Contribution: The research adds to the body of knowledge about developing nations, on the nexus of VAIC and financial performance. It reiterates the point that firms should emphasize intellectual capital accounting and disclosure to boost and maintain a motivated workforce and its potentially beneficial effect on firm valuation in this knowledge era.
Protein Expression Redirects Vesicular Stomatitis Virus RNA Synthesis to Cytoplasmic Inclusions

Positive-strand and double-strand RNA viruses typically compartmentalize their replication machinery in infected cells. This is thought to shield viral RNA from detection by innate immune sensors and favor RNA synthesis. The picture for the non-segmented negative-strand (NNS) RNA viruses, however, is less clear. Working with vesicular stomatitis virus (VSV), a prototype of the NNS RNA viruses, we examined the location of the viral replication machinery and RNA synthesis in cells. By short-term labeling of viral RNA with 5′-bromouridine 5′-triphosphate (BrUTP), we demonstrate that primary mRNA synthesis occurs throughout the host cell cytoplasm. Protein synthesis results in the formation of inclusions that contain the viral RNA synthesis machinery and become the predominant sites of mRNA synthesis in the cell. Disruption of the microtubule network by treatment of cells with nocodazole leads to the accumulation of viral mRNA in discrete structures that decorate the surface of the inclusions. By pulse-chase analysis of the mRNA, we find that viral transcripts synthesized at the inclusions are transported away from the inclusions in a microtubule-dependent manner. Metabolic labeling of viral proteins revealed that inhibiting this transport step diminished the rate of translation. Collectively those data suggest that microtubule-dependent transport of viral mRNAs from inclusions facilitates their translation. Our experiments also show that during a VSV infection, protein synthesis is required to redirect viral RNA synthesis to intracytoplasmic inclusions. As viral RNA synthesis is initially unrestricted, we speculate that its subsequent confinement to inclusions might reflect a cellular response to infection.
Comprehensive Review of In Vitro Human Follicle Development for Fertility Restoration: Recent Achievements, Current Challenges, and Future Optimization Strategies

Ovarian tissue cryopreservation (OTC) and subsequent transplantation (OTT) is a fertility preservation technique widely offered to prepubertal girls and young fertile women who need to undergo oncological treatment but are at a high risk of infertility. However, OTT is not considered safe in patients with certain diseases like leukemia, Burkitt’s lymphoma, and ovarian cancer because of the associated risk of malignant cell reintroduction. In vitro follicle development has therefore emerged as a promising means of obtaining mature metaphase II (MII) oocytes from the primordial follicle (PMF) pool contained within cryopreserved ovarian tissue, without the need for transplantation. Despite its significant potential, this novel approach remains highly challenging, as it requires replication of the intricate process of intraovarian folliculogenesis. Recent advances in multi-step in vitro culture (IVC) systems, tailored to the specific needs of each follicle stage, have demonstrated the feasibility of generating mature oocytes (MII) from early-stage human follicles. While significant progress has been made, there is still room for improvement in terms of efficiency and productivity, and a long way to go before this IVC approach can be implemented in a clinical setting. This comprehensive review outlines the most significant improvements in recent years, current limitations, and future optimization strategies.
An approach to joint sequential detection and estimation with distributional uncertainties

Joint detection and estimation is an important yet little-studied problem that arises in many signal processing applications. In this paper, a sequential and robust solution approach is presented. To design the test fulfilling constraints on the error probabilities and the quality of the estimate, the problem is converted into an unconstrained form and subsequently solved using Linear Programming. To handle model uncertainties, a band model for both hypotheses is used and a concept for determining the pair of least favorable distributions is adopted to devise a robust detection scheme. For the robust estimation, an upper bound of the estimation cost, based on maximizing a Kullback-Leibler divergence, is derived. The resulting test meets the specifications on the error probabilities and the quality of the estimate for every feasible pair of distributions. Numerical results are provided for the pair of least favorable distributions and for a pair of randomly selected distributions.
Allergen-Specific IgG Antibodies Purified from Mite-Allergic Patients Sera Block the IgE Recognition of Dermatophagoides pteronyssinus Antigens: An In Vitro Study

One of the purposes of specific immunotherapy (SIT) is to modulate humoral immune response against allergens with significant increases in allergen-specific IgG levels, commonly associated with blocking activity. The present study investigated in vitro blocking activity of allergen-specific IgG antibodies on IgE reactivity to Dermatophagoides pteronyssinus (Dpt) in sera from atopic patients. Dpt-specific IgG antibodies were purified by ammonium sulfate precipitation followed by protein-G affinity chromatography. Purity was checked by SDS-PAGE and immunoreactivity by slot-blot and immunoblot assays. The blocking activity was evaluated by inhibition ELISA. The electrophoretic profile of the ammonium sulfate precipitated fraction showed strongly stained bands in ligand fraction after chromatography, compatible with molecular weight of human whole IgG molecule. The purity degree was confirmed by detecting strong immunoreactivity to IgG, negligible to IgA, and no reactivity to IgE and IgM. Dpt-specific IgG fraction was capable of significantly reducing levels of IgE anti-Dpt, resulting in 35%–51% inhibition of IgE reactivity to Dpt in atopic patients sera. This study showed that allergen-specific IgG antibodies purified from mite-allergic patients sera block the IgE recognition of Dermatophagoides pteronyssinus antigens. This approach reinforces that intermittent measurement of serum allergen-specific IgG antibodies will be an important objective laboratorial parameter that will help specialists to follow their patients under SIT.
Targeting the DNA replication checkpoint by pharmacologic inhibition of Chk1 kinase: a strategy to sensitize APC mutant colon cancer cells to 5-fluorouracil chemotherapy

5-fluorouracil (5-FU) is the first line component used in colorectal cancer (CRC) therapy however even in combination with other chemotherapeutic drugs recurrence is common. Mutations of the adenomatous polyposis coli (APC) gene are considered as the initiating step of transformation in familial and sporadic CRCs. We have previously shown that APC regulates the cellular response to DNA replication stress and recently hypothesized that APC mutations might therefore influence 5-FU resistance. To test this, we compared CRC cell lines and show that those expressing truncated APC exhibit a limited response to 5-FU and arrest in G1/S-phase without undergoing lethal damage, unlike cells expressing wild-type APC. In SW480 APC-mutant CRC cells, 5-FU-dependent apoptosis was restored after transient expression of full length APC, indicating a direct link between APC and drug response. Furthermore, we could increase sensitivity of APC truncated cells to 5-FU by inactivating the Chk1 kinase using drug treatment or siRNA-mediated knockdown. Our findings identify mutant APC as a potential tumor biomarker of resistance to 5-FU, and importantly we show that APC-mutant CRC cells can be made more sensitive to 5-FU by use of Chk1 inhibitors.
Likely Transgender Individuals in U.S. Federal Administrative Records and the 2010 Census

This paper utilizes changes to individualsâ€™ first names and sex-coding in files from the Social Security Administration (SSA) to identify people likely to be transgender. I first document trends in these transgender-consistent changes and compare them to trends in other types of changes to personal information. I find that transgender-consistent changes are present as early as 1936 and have grown with non-transgender consistent changes. Of the likely transgender individuals alive during 2010, the majority change their names but not their sex-coding. Of those who changed both their names and their sex-coding, most change both pieces of information concurrently, although over a quarter change their name first and their sex-coding 5-6 years later. Linking individuals to their 2010 Census responses shows my approach identifies more transgender members of racial and ethnic minority groups than other studies using, for example, anonymous online surveys. Finally, states with the highest proportion of likely transgender residents have state-wide laws prohibiting discrimination on the basis of gender identity or expression. States with the lowest proportion do not.