Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching and Supervision in Counseling Teaching and Supervision in Counseling

Counselor educators are expected to engage in research and mentor doctoral students, highlighting the importance of competency in both areas. Grit predicts positive work outcomes, and we found no studies on grit in relation to counselor educator success measures. We wanted to understand the role of grit in counselor education productivity levels and necessary competencies. We recruited counselor educators at CACREP-accredited institutions with doctoral programs. We hypothesized that grit would predict both mentoring competencies and publication rates, mediated by research competencies. We tested a model with counselor educators ( N = 110) and found that the relationship between grit, as measured by the Short Grit Scale, and mentoring competency, as measured by the Mentoring Competency Assessment, and the relationship between grit and number of total career publications were both partially mediated by research competencies, as measured by the Research Competencies Scale. Thus, grit is directly and indirectly related to publications and mentoring competency. Implications for counselor educators include maintaining grit and how to use self-assessment of research and mentoring competency to increase productivity.
3D Angle-of-Arrival Estimation with Practical Antenna Conﬁgurations

—With the advances in Internet of Things (IoT) and mobile connectivity, location-based services (LBSs) are increasingly popular and continue to enhance our experience. Multiple antennas have been pivotal for the provision of reliable wireless communications and high-resolution localization. However, in the real world, mobile handsets tend to have very limited space and the incorporation of multiple antennas hardly obeys the rule of half-wavelength separation between antenna elements, resulting in complex mutual coupling. More often than not, antennas are placed not to affect negatively the artistic design and handling of the device. The irregular 3D radiation pattern of each antenna element further impairs the capability of the antenna array for localization. In this paper, we propose a generic parametric model that can incorporate the actual antenna responses into the angle-of-arrival (AoA) estimation. As a result, we present an efﬁcient algorithm to enable 3D AoA estimation on mobile phones based on the proposed model, and test it on a 5G phone at a midband spectrum with 100MHz channel bandwidth. Our results reveal promising performance with over 90% scenarios where the AoA estimation errors are lower than 10 ◦ on a mobile phone.
MIT Open Access Articles Turning a Shove into a Nudge? A “Labeled Cash Transfer” for Education

Conditional Cash Transfers ( CCTs ) have been shown to increase human capital investments , but their standard features make them expensive. We use a large randomized experiment in Morocco to estimate an alternative government-run program , a “labeled cash trans-fer” ( LCT ) : a small cash transfer made to fathers of school-aged children in poor rural communities , not conditional on school attendance but explicitly labeled as an education support program. We document large gains in school participation. Adding conditionality and targeting mothers made almost no difference in our context. The program increased parents’ belief that education was a worthwhile investment , a likely pathway for the results. ( JEL H23, I24, 128, I38, J24, O15, O18 ) This paper evaluates the impact of a “labeled cash transfer” ( LCT ) . The program we evaluate features small transfers, targeted to poor communities ( with all households eligible in those communities ) , and paid out to fathers. The program is uncon-ditional but retains an implicit endorsement of education through its school-based enrollment procedure. This program was designed and implemented on a ( randomized ) pilot basis by Morocco’s Ministry of Education. Within the same experiment, conducted over 600 communities, we compared it to three variants: ( i ) making the transfer explicitly conditional on regular attendance, ( ii ) making payments to mothers instead of fathers, and ( iii ) doing both at the same time.
MIT Open Access Articles Accelerated Dual Descent for Network Optimization

—Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rates are typically very slow. This paper introduces a family of dual descent algorithms that use approximate Newton directions to accelerate the convergence rate of conventional dual descent. These approximate directions can be computed using local information exchanges thereby retaining the beneﬁts of distributed implementations. The approximate Newton directions are obtained through matrix splitting techniques and sparse Taylor approximations of the inverse Hessian. We show that, similarly to conventional Newton methods, the proposed algorithm exhibits superlinear convergence within a neighborhood of the optimal value. Numerical analysis corroborates that convergence times are between one to two orders of magnitude faster than existing distributed optimization methods. A connection with recent developments that use consensus iterations to compute approximate Newton directions is also presented.
The Relationship Between Protein Types and hs-CRP on eGFR

Few studies have measured the relationship between protein types and inflammation on kidney function among US adults. This study’s objective was to identify the relationship between protein types (animal, dairy, plant, seafood) and high-sensitivity C-reactive protein on estimated glomerular filtration rate (eGFR). A cross-sectional secondary analysis using NHANES 2017-2018 data was performed on 4252 adults with an eGFR of >15 ml/min/1.73m2. At least one 24-hour recall was used to categorize the protein type. Descriptives, frequencies, Pearson correlation, and multiple linear regressions were conducted using SPSS v28 with a significance of p<0.05. Participants were mostly female (50.1%), had a mean age of 50.1 years, and self-identified as non-Hispanic White (36.5%). A majority consumed animal and dairy products compared to seafood and plant products. A negative association was observed between consumption of plant proteins and inflammation on eGFR (p<0.05). In the adjusted regression model, non-Hispanic Black race had a positive influence on eGFR, female and age had negative influences on eGFR (p < 0.001), with no statistical significance seen with one identifying as male or other races. Reduced consumption of plant proteins with elevated inflammation can decline kidney function. Future studies should focus on frequency and amount of proteins consumed and inflammation to reduce the progression of chronic diseases such as kidney disease.
Carbonated Yogurt—Sensory Properties and Consumer Acceptance 1

Sweetened low fat (1%) plain yogurt and low fat Swiss-style strawberry and lemon yogurts were manufactured using cream, nonfat dry milk, sugar, stabilizer (a blend of modified food starch, carragee-nan, and pectin), and skim milk. After addition of the yogurt cultures and Lactobacillus acidophilus and Bi-fidobacterium longum , yogurt samples were incubated at 43 ° C until desirable pH values of 5.0 or 4.2 were reached. Carbon dioxide (0.08 to 0.09 kg/cm 2 ) was incorporated into the cooled, flavored yogurt by way of a sanitary hose. The yogurt was stored at 4 ° C for sensory evaluation by an expert panel on d 7, 21, and 45. A consumer panel evaluated carbonated and noncarbonated yogurts on d 21. The results of the study showed that the carbonation had no significant effect on the acceptability of yogurt during shelf-life. Also, the carbon dioxide treatment did not alter the sensory characteristics of yogurt as noted either by expert panelists or by consumers.
Crystal Structure and Intermolecular Energy for Some Nandrolone Esters

Nandrolone (Estr-4-en-17β-ol-3-one) is a derivative of testosterone and a naturally occurring anabolic–androgenic agent which belongs to the steroid group. Crystal structures of four short, medium and long esterified forms of nandrolone, including propionate, phenylpropionate, cypionate and undecanoate were determined using single-crystal X-ray diffraction. Crystal packing, supramolecular features and intermolecular interactions were described based on a quantitative and qualitative Hirshfeld surfaces analysis accompanied by evaluation of crystal energies and intermolecular interactions computation. Also, the solubility of the esters was investigated from a pharmaceutical perspective.
Effect of hydroxytyrosol, Moringa, and spirulina on the physicochemical properties and nutritional characteristics of gluten‐free brownies

Abstract Brownies, enriched with fiber and Moringa oleifera, hydroxytyrosol (HXT), and spirulina (encapsulated and nonencapsulated), and dietary fiber using psyllium were elaborated. For that, a commercial control (CTRL) and an experimental control (CTRL) (without antioxidants) were compared. Color, nutritional composition, pH, antioxidant capacity, total phenolic compounds, as well as sensory properties were evaluated. The results showed the brownies developed with psyllium and the different extracts increased total dietary fiber compared to CTRL Commercial and CTRL, with E‐spirulina (14.93 g/100 g) and Moringa (11.91 g/100 g) being the most prominent samples. However, with regard to soluble fiber, the highest content of NE‐spirulina and the lowest content of HXT were observed. In addition, brownies enriched with extracts showed higher antioxidant capacity and higher phenolic compounds than controls, with HXT standing out at 299.25 μM Trolox/g in ABTS, 1470.08 μM Trolox/g in DPPH, and 18.15 μM Trolox/g in FRAP. However, a high level of phenolic compounds was found in E‐Spirulina (604.71 mg/L). In reference to fatty acids, monounsaturated fatty acids (MUFA) (70%) were the predominant fatty acids, followed by polyunsaturated fatty acids (PUFA) (19%) and saturated fatty acids (SFA) (10%). Glutamic acid and asparagine were the predominant amino acids. As for mineral content, N‐spirulina and E‐spirulina were the brownies with the highest iron bioaccessibility; Si, Na, B, Al, P, Fe, Zn, Bi, Ca, Cu, Mg, Mn, Rb, S, and Sr being the most abundant elements in the brownies of this study. In addition, the HXT and Moringa samples scored higher in overall acceptability compared to the controls. The findings suggest that the incorporation of psyllium, quinoa flour, and antioxidant extracts in brownies could be a viable approach to produce a healthy brownie enriched with fiber, antioxidants and, therefore, considering the nutritional, physicochemical, and organoleptic characteristics, HTX is the ideal compound to enrich bakery products.
Benign Structures. The Worldview of Danish National Poet, Pastor, and Politician N.F.S. Grundtvig (1783-1872)

This paper presents a study of the central Danish 19th-century figure N.F. S. Grundtvig (1783-1872) and his worldview. More precisely, by way of simple neural word embeddings we seek to plot Grundtvig’s worldview in attempt to tease out factors explaining for his cultural and religious success as a poet. We arrive at the conclusion that one factor for Grundtvig’s relative success could be found in his explicitly positive worldview fit for modern conditions.
Identification of subunit-specific and antagonist-specific amino acid residues in the NMDA receptor glutamate binding pocket

The resolved X-ray crystal structures of the glutamate binding domain (S1/S2 domains) of the GluR2 and NR1 glutamate receptor subunits were used to model the homologous regions of the N-methyl-D-aspartate (NMDA) receptor’s NR2 subunits. To test the predictive value of these models, all four stereoisomers of the antagonist 1-(phenanthren-2-carbonyl) piperazine-2,3-dicarboxylic acid (PPDA) were docked into the NR2B glutamate-binding site model. This analysis suggested an affinity order for the PPDA isomers of D-cis > L-cis > L-trans = D-trans and predicted that the 2-position carboxylate group of the cis -PPDA isomers, but not of the trans -PPDA isomers, may be interacting with histidine 486 in NR2B. Consistent with these predictions, cis -PPDA displays an 35-fold higher affinity for NR2B-containing NMDA receptors than trans - PPDA. In addition, mutating NR2B’s H486 to phenylalanine decreased cis -PPDA affinity 8-fold, but had no effect on trans -PPDA affinity. In contrast, the NR2B H486F mutation increased the affinity of the typical antagonists (2 R *,4 S *)-4-phosphonomethyl- 2-piperidine carboxylic acid (CGS-19755) and 4-(3-phosphonopropyl) piperidine-2-carboxylic acid (PPPA). In the NR1-based NR2 models, there were only 4 subunit-specific amino acid residues exposed to the ligand-binding pocket (and 6 in the GluR2-based models). These residues are located at the edge of the binding pocket, suggesting that large antagonists may be necessary for subtype-specificity. Of these residues, mutational analysis and modeling suggest that A414, R712 and G713 (NR2B numbering) may be especially useful for developing NR2C and NR2D-selective NMDA
SMART-ETL-MR: NOVEL ETL FRAMEWORK FOR BUILDING DATA WAREHOUSE FROM BIG DATA SOURCE USING MAPREDUCE

The concept of Big Data created to face the massive explosion of data produced from web 2.0, smart devices, sensors, social networks platforms like Facebook, Twitter, Instagram, LinkedIn, has increased continuously. However, new challenges and opportunities appear due to the growth of data. Nevertheless, several prominent organizations and companies have realized that data is valuable and offers competitive advantages, great benefits, and relevant knowledge when it gets converted to actionable information they can use. However, collecting these massive data is not enough, as we should be able to integrate and analyze these data pulled from different heterogeneous sources after loading them to improve analysis goals. This research article's primary objective is to adapt the ETL (extraction transformation-loading) processes with the potential of Big Data technologies in order to deal with these new challenges from data warehousing perspective and knowledge discovery that directly impacts business decision-making systems. In this article, a new approach based called SMART-ETL-MR presented on the Map-Reduce paradigm to expedite data handling and to build a well-organized data warehouse. Experimental results prove that the ETL operation performs successfully with optimal algorithms.
Evaluating the E�cacy of EEG Features and Data Fusion in Migraine Diagnosis

This study investigates the potential of using EEG features for the diagnosis of migraine. The asymmetry, phase synchronization, and relative power spectra of EEG signals were analyzed in 10 migraineurs and 10 healthy subjects. The objective of the study is to ascertain the relative importance of distinct characteristics in migraine diagnosis and establish a more effective classi�er model for a limited dataset application. Singular features displayed inadequate accuracy in migraine classi�cation under no photic stimulation, with an accuracy of roughly 70%. However, data fusion using the Random Forest algorithm resulted in a 5% increase in accuracy, achieving an accuracy of 75% with no photic stimulation and 88% under 3Hz photic stimulation. Results indicates that Random Forest is the most e�cient classi�er model for the identi�cation of migraine utilizing a small dataset with numerous characteristics. The study presents innovative perspectives into the e�cacy of amalgamating multiple well-known EEG abnormalities for migraine diagnosis and highlights the signi�cance of meticulous deliberation of the choice of classi�cation model and the scale of the dataset in constructing precise and dependable diagnostic tools for migraine. The �ndings demonstrate the potential for future studies to explore additional characteristics and algorithms to boost the accuracy of migraine classi�cation. This investigation contributes to the burgeoning collection of research in the �eld of migraine diagnosis and presents a foundation for further inquiry into the amalgamation of multiple characteristics and the effectiveness of distinct methods.
High-Accuracy Injection Using a Mobile Manipulation Robot for Chemistry Lab Automation

Lab automation has the potential to accelerate scientific progress in the natural sciences, allowing tedious experiments that would require many hours of human time to be automated, enabling higher accuracy, efficiency, and repeatability. Mobile manipulation robots have the potential to work in chemistry labs designed for humans to complete tasks for which setting up customized factory-scale automation is premature or infeasible. We present a new method to enable a mobile manipulation robot to automate injections, a common task in chemistry labs when using equipment such as gas chromatographs (GCs) for analyzing the contents of a sample mixture. This task is challenging for a mobile manipulation robot due to the need to navigate to the equipment in the lab and then achieve millimeter-scale accuracy required for the syringe positioning. Our approach leverages deep learning to create a model capable of localizing the syringe with high accuracy using cameras mounted on the chemistry equipment, and then uses a visual servoing approach based on the syringe's needle localization to achieve the injection. We demonstrate that our approach is robust to uncertainty in navigation as well as uncertainty in the grasping position and orientation of the syringe, achieving errors sufficiently small to enable the mobile manipulation robot to automate injections in real chemistry equipment.
ROBUST FEATURE SELECTION WITH CHICKEN SWARM INTELLIGENCE IMPROVED MULTILAYER PERCEPTRON FOR EARLY DETECTION OF MENTAL ILLNESS DISORDER

Mental illness is a kind of health condition highly impacts a person’s emotions, mind and their behavior. When mental disorder is not diagnosed at its earlier condition it results in depression, anxiety, schizophrenia, autism etc., are extremely widespread today. Recently many machine learning methods have been developed to help experts such as psychologists’ and psychiatrists’ for making decision regarding mental health of patient based on historical data of the patients. However conventional machine learning methods require optimal performance of feature engineering to obtained better performance and reduce computation complexity. This paper focuses on developing improved multilayer perceptron its objective is to handle over fitting, fine-tuning parameter values by integrating optimized feature selection and adopting mimetic meta heuristic model. LASSO (Least Absolute Shrinkage and Selection Operator) model-based feature selection is used for discovering best feature subset because it controls over fitting and prediction error with the help of ridge regression. In improved MLP instead of using trial and error based random parameter value assignment it inherits the Intelligence of Chicken Swam behavior. The best fittest value is assigned to the parameters of MLP (Multi-Layer Perceptron) to improve the accuracy rate of mental illness disorder detection. The simulation results are conducted on OSMI 2019 dataset and the outcome proved that CSI-MLP accomplished highest rate of accuracy in early detection of mental illness disorder compared to other conventional models.
Polymorphism in maternal HLA-DRB5 is associated with the risk of preeclampsia in Chinese population

Background: Preeclampsia is an important clinical syndrome occurring during pregnancy. It shows genetic disposition, and the genetic risk has large ethnic heterogeneity. The study was designed to investigate the genetic risk of preeclampsia in Chinese pregnancies, and to apply it in early screening of the disease. Methods: We performed a genome-wide association study to screen candidate risk loci associated with preeclampsia in Chinese people, and validated them with an independent cohort of enlarged size. We also trained prediction models using the genotypes of newly identi�ed risk loci to screen the pregnancies with high preeclampsia risk. Results: A segment in chromosome 6 covering HLA-DQB1, HLA-DRB5 and other immune-related genes shows the most signi�cant association, and three loci in HLA-DRB5 were con�rmed with an enlarged validation cohort. One of the validated loci, rs147440497, forms an amino acid change by the nucleotide polymorphism, which further causes a conformational change in the antigen-binding domain of HLA-DRB5 protein. With the genotypes of risk genetic loci and other demographic features, a machine-learning model was trained, which can predict Chinese preeclampsia pregnancies accurately, with a cross-validated recalling rate of 0.63 at a false positive rate of 8%. Conclusion: We identi�ed a novel gene from maternal genome, HLA-DRB5, the polymorphism in which is associated with preeclampsia. The genotypes of risk SNP loci can also be used for prediction of preeclampsia risk in Chinese population accurately.
Etiology of narrow maxilla creating orthodontic and prosthetic treatment difficulties.

OBJECTIVE Narrow maxilla occurring due to various congenital or acquired causes creates major orthodontic problems and complicates prosthetic dental rehabilitation. The etiologic factors are mostly related to upper airway pathologies that restrict breathing and cause negative pressure at the base of the nose and nasopharynx. The upper and lower airway is a whole unit. Regional anomalies or acquired problems affect the entire system. This can lead to developmental issues and permanent disorders in childhood, which will last their real life. This study was planned to investigate the incidence of nasopharyngeal obstruction originating from allergic rhinitis, turbinate hypertrophy, septum deviation, and adenoid vegetation in children scheduled for orthodontic treatment due to maxillary stenosis. PATIENTS AND METHODS Our study group consists of one hundred children aged 12-16 years who applied to the orthodontist due to dental malalignment and were found to have a narrowing of the maxilla. After the orthodontic evaluation, the patients were referred for an ENT examination to evaluate the etiological factors originating from the upper respiratory tract. In the study group, nasal congestion and allergic rhinitis were first investigated. All symptoms were evaluated and scored. Then, an ENT physical examination was performed in all cases, and nasal cavities, nasopharynx, and oropharynx were assessed with a fiberoptic endoscope. Regarding etiological factors, allergic rhinitis, turbinate hypertrophy, nasal septum deviation, and adenoid vegetation that would prevent breathing were carefully investigated. RESULTS Firstly, deep palate, narrowed maxillary arch, V-shaped arch, adenoid face type, bilateral posterior crossbite, insufficient lip presence, maxillary incisor protrusion (upper forward thrust), skeletal class 2 division 1 malocclusion, and increased lower face height detected in patients primarily diagnoses were grouped according to their pathologies. Allergic rhinitis was found in 43 cases, turbinate hypertrophy in 30 instances, nasal septum deviation in 18 cases, and adenoid vegetation that prevented respiration in 61 patients. CONCLUSIONS It is known that increased nasal airway resistance due to allergic rhinitis, septal deviation, turbinate hypertrophy, or adenoid vegetation in the upper respiratory tract may lead to permanent orthodontic disorders in children and adolescents. A multidisciplinary approach, early diagnosis, and treatment should be the first step to prevent this situation. Secondly, it should be planned to correct the anatomical disorders that have occurred with appliances and, if necessary, surgical approaches. Taking precautions before permanent problems arise in childhood is also crucial in prosthetic dentistry.