Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliability Generalization (RG) of the Counseling Center Assessment of Psychological Symptoms (CCAPS)

Due to an increased usage of college counseling centers in the treatment of mental health concerns, it is imperative that centers implement appropriate assessments of psychological symptoms. We examined the Counseling Center Assessment of Psychological Symptoms (CCAPS), which was designed as a routine instrument to assess a range of mental health symptoms. Proper assessment and reporting of reliability are essential before one can meaningfully interpret assessment outcomes. This study employed a meta-analytic technique, Reliability Generalization (RG), to examine reporting practices, and analyze the reported CCAPS reliability estimates. Additionally, reported CCAPS reliability estimates were analyzed in order to assess diversity variables, which can affect the measurement of psychological symptoms and distress. Only 22% (N = 12) of the 54 total research studies reported reliability estimates for the CCAPS. Most studies cited a previous source and others simply noted that the measure was “reliable” (66%; N = 25). More information is needed for subscale reliability since the current CCAPS Cronbach’s alphas ranged from fair to excellent (> 0.60 - > 0.80). An increase in reliability reporting is needed to examine the CCAPS’ use in various sample populations. Implications for reliability reporting standards are discussed. Key words: Reliability Generalization, Counseling Center Assessment of Psychological Symptoms (CCAPS), reliability reporting, meta-analysis.
A genetic interaction map centered on cohesin reveals auxiliary factors in sister chromatid cohesion.

Eukaryotic chromosomes are replicated in interphase and the two newly duplicated sister chromatids are held together by the cohesin complex and several cohesin auxiliary factors. Sister chromatid cohesion is essential for accurate chromosome segregation during mitosis, yet has also been implicated in other processes, including DNA damage repair, transcription and DNA replication. To assess how cohesin and associated factors functionally interconnect and coordinate with other cellular processes, we systematically mapped genetic interactions of 17 cohesin genes centered on quantitative growth measurements of >52,000 gene pairs in budding yeast. Integration of synthetic genetic interactions unveiled a cohesin functional map that constitutes 373 genetic interactions, revealing novel functional connections with post-replication repair, microtubule organization and protein folding. Accordingly, we show that the microtubule-associated protein Irc15 and the prefoldin complex members Gim3, Gim4 and Yke2 are new factors involved in sister chromatid cohesion. Our genetic interaction map thus provides a unique resource for further identification and functional interrogation of cohesin proteins. Since mutations in cohesin proteins have been associated with cohesinopathies and cancer, it may also identify cohesin interactions relevant in disease etiology.
REINFORCED OF PIERS OF A BRIDGE TYPE USING FRAGILITY CURVES

Most of the existing bridges in Mexico were built 30 years ago or more (similar to that of other countries), so maintenance and reinforced programs are necessary to rehabilitate old structures before earthquakes take place. To define the best rehabilitation technique depends on the bridge type, damage degree of the elements, earthquake characteristics and economic aspects. Most of the time, the reinforcement condition is decided for each special case. This paper presents a reinforcement procedure to define the best rehabilitation technique of piers of a bridge type, with single wall pier by bent. The best rehabilitation technique is defined in function of probabilistic aspects, using fragility curves. To do this, mechanical properties of the piers material are considered as random variables with probabilistic distribution function, mean and variation coefficient are considered from the available literature. Also, earthquake load is random considering four seismic scenarios and artificial records. For the original structures the fragility curves were defined by means of a Monte Carlo simulation for the four seismic scenarios. Damage is represented by the local and global Park indices. Then, light, moderate and severe damage were simulated in most earthquake susceptible pier. Damage is simulated considering degradation of pier section in function of experimental test reported in literature. For example, light damage, almost 10% of degradation, is represented by the same original section without concrete cover, because it was observed in experimental test of piers elements that the concrete cover is lost in a few cycles. For damaged structures fragility curves were again determined. Degraded bridges were reinforced using conventional techniques, specifically steel, concrete and fiber jackets, only for the damaged piers. The dimensions of the jackets were first selected considering that the fragility curves of these structures were similar to the ones of the original bridges. But it was not always possible; for example the minimum thick recommended produces a null damage index in the most of the Monte Carlo simulation of elements with light damage. Fragility curves of original, damaged and reinforced bridges were compared. Through this comparison, the best option to reinforce the bridge piers is selected, and some practical recommendations were expressed.
Recent development in Graphene technology for multidisciplinary properties and its applications: A Review

Among distinct 2-D materials, Graphene has attained higher potential due to its attractive properties. This material provided a new dimension to nanotechnology and material research. It has a 2D honeycomb structure lattice having a single layer of carbon atoms due to which it is flexible in nature, durable and lighter than any material. It has a wide range of applications starting from the fabrication of products, biological engineering, optical electronics, electrical engineering, and biomedical field. Morden Graphene's research has been directed towards the exploration of electronic properties and their electron transfer properties. This attracts the interest of scientists and engineers to come up with new theories and technologies. Experiments are conducted on Graphene to discover new features suitable for different area of interests. Graphene is among one of the materials which are undergoing intense research due to its fascinating properties from the last 2-3 decades. In this review paper, some basic properties of Graphene are discussed, followed by their respective applications, and then-current research in Graphene is explored. Overall this paper gives an overview of Graphene in terms of properties and its applications, especially in the medical sector, which will enlighten future research in the field of material science. KeywordsGraphene, 2D Materials, Applications of Graphene, Protective Coatings.
AN APPLICATION OF ELECTRON MICROSCOPIC CYTOCHEMISTRY TO HUMAN TUMORS

Prostatic carcinoma, renal cell carcinoma and melanoma were studied by electron microscopic enzyme cytochemistry. ACPase of prostatic cancer cells was found in lysosomes, secretory vacuoles and vesicles as well as some Golgi apparatuses. The enzyme localizations remained unchanged in tumor cells two weeks after castration when cells were viable. Renal cell carcinomas revealed to have positive ALPase activity at microvilli resembling brush border and lateral plasma membranes facing adjacent tumor cells. The enzyme was negative at basal plasma membrane of the tumor cells. Proximal tubule cells of human kidney showed ALPase activity only at apical membranes. This indicated functional dedifferentiation of plasma membrane in the tumor cells. These observations were verified and substantiated by TPPase, IDPase and G6Pase localizations in tumor cells. The tumor cells also showed positive G6Pase in endoplasmic reticulum. DOPA oxidase was successfully detected in smooth endoplasmic reticulum close to Golgi apparatus, innermost Golgi cisternae and premelanosomes both in cultured melanoma cells and melanoma tissues, which may have diagnostic value. Thus, EM enzyme cytochemistry was considered to be applicable and useful for human cancer study concerning histogenesis, diagnosis and to assess the treatment.
PRINCIPAL REQUIREMENTS OF DESIGNING THE REWARD-PENALTY SCHEMES FOR RELIABILITY IMPROVEMENT IN DISTRIBUTION SYSTEMS

An important consequence of restructuring in the power industry is the emergence of service quality regulation in the distribution network. Reward/Penalty Scheme (RPS) is regulated to assure the service reliability. RPS is a financial tool designed by regulator to prevent the service reliability deterioration. RPS rewards the utility who is providing good reliability and penalizes the utility who is providing poor reliability. This paper investigates the main requirements for designing and implementing of an effective RPS. It describes that the conditions of country that implements the RPS such as ownership of distribution utilities (i.e. private or public), regulation of tariff setting, subsidizing the electricity, regulatory policy, and other factors force the regulator to set a unique scheme for reward and penalty. The aim of this paper is to comprehensively describe the different types of RPS based on the mentioned factors.
Phylogeny and historical biogeography of leafhopper subfamily Iassinae (Hemiptera: Cicadellidae) with a revised tribal classification based on morphological and molecular data

Phylogenetic relationships among major lineages of the leafhopper subfamily Iassinae were explored by analysing a dataset of 91 discrete morphological characters and DNA sequence data from nuclear 28S rDNA and histone H3 genes and mitochondrial 12S rDNA. Bayesian, maximum‐likelihood and maximum parsimony analyses yielded similar tree topologies that were well resolved with strong branch support except at the base of the tree, resulting in equivocal support for inclusion of Bythoniini as a tribe of Iassinae but strong support for the monophyly of Iassinae (excluding Bythoniini) and most previously recognized iassine tribes. Divergence times for recovered nodes were estimated using a Bayesian relaxed clock method with two fossil calibration points. The results suggest that the deepest divergences coincided with Gondwanan vicariant events but that more recent divergences resulted from long‐range dispersal and colonization. Biogeographical analyses suggest that the group most likely has a Neotropical origin. The following changes to the taxonomic classification are proposed: establishment of three new tribes, Batracomorphini trib.n. (based on type genus Batracomorphus Lewis), Hoplojassini trib.n. (based on type genus Hoplojassus Dietrich and including one other South American genus), Lipokrisnini trib.n. (based on type genus Lipokrisna Freytag and including two other endemic Caribbean genera); Krisnini is redefined to include only the Old World genera Krisna and Gessius; Iassini is redefined to include only the type genus and four endemic Afrotropical genera; Bascarrhinus Fowler and Platyhynna Berg, recently treated as genera incertae sedis, are placed in Hyalojassini; Thalattoscopus Kirkaldy is added to the previously monobasic tribe Trocnadini. Iassinae now includes 12 tribes, all of which appear to be monophyletic. Revised morphological diagnoses of the subfamily and each of the included tribes are provided and a key to tribes is also given.
Edinburgh Research Explorer Autonomous Driving with Interpretable Goal Recognition and Monte Carlo Tree Search

—The ability to predict the intentions and driving trajectories of other vehicles is a key problem for autonomous driving. We propose an integrated planning and prediction system which leverages the computational beneﬁt of using a ﬁnite space of maneuvers, and extend the approach to planning and prediction of sequences of maneuvers via rational inverse planning to recognise the goals of other vehicles. Goal recognition informs a Monte Carlo Tree Search (MCTS) algorithm to plan optimal maneuvers for the ego vehicle. Our system constructs plans which are explainable by means of rationality . Evaluation in simulations of four urban driving scenarios demonstrate the system’s ability to robustly recognise the goals of other vehicles while generating near-optimal plans.
Parameter Estimation of Induction Machine Single-Cage and Double-Cage Models Using a Hybrid Simulated Annealing–Evaporation Rate Water Cycle Algorithm

This paper presents the usage of the hybrid simulated annealing—evaporation rate water cycle algorithm (SA-ERWCA) for induction machine equivalent circuit parameter estimation. The proposed algorithm is applied to nameplate data, measured data found in the literature, and data measured experimentally on a laboratory three-phase induction machine operating as an induction motor and as an induction generator. Furthermore, the proposed method is applied to both single-cage and double-cage equivalent circuit models. The accuracy and applicability of the proposed SA-ERWCA are intensively investigated, comparing the machine output characteristics determined by using SA-ERWCA parameters with corresponding characteristics obtained by using parameters determined using known methods from the literature. Also, the comparison of the SA-ERWCA with classic ERWCA and other algorithms used in the literature for induction machine parameter estimation is presented. The obtained results show that the proposed algorithm is a very effective and accurate method for induction machine parameter estimation. Furthermore, it is shown that the SA-ERWCA has the best convergence characteristics compared to other algorithms for induction machine parameter estimation in the literature.
Bucket of Ignorance: A Hybrid Data Structure for Timing Mechanism in Real-Time Operating Systems

—To maintain deterministic timing behaviors, Real-Time Operating Systems (RTOSes) require not only a task scheduler but also a timing mechanism for the periodicity of recurrent tasks. Most of existing open-source RTOSes implement either a tree-based or a list-based mechanism to track which task is ready to release on-the-ﬂy. Although tree-based mechanisms are known to be efﬁcient in time complexity for searching operations, the additional effort processing removals and insertions are also not negligible, which may countervail the advantage, compared to list-based timer-managers, even with small task sets. In this work, we provide a simulation framework, which is ready to be released, to investigate existing timing mechanisms and analyze how do they perform under certain conditions. Throughout extensive simulations, we show that our proposed solution indeed requires less computation effort than conventional timing mechanisms when the size of task set is in the range of 16 to 208 .
Identification of Crop Diseases using Deep Learning

: Crop diseases and harmful insects are a main challenge in the agriculture sector quick and an accurate prediction of crop diseases could help to develop an early treatment technique while considerably reducing economic losses Modern advanced developments in Deep Learning have allowed researchers to extremely improve the performance and accuracy of object detection and recognition systems we proposed a deep-learning-based approach to detect leaf diseases in many different crops using images of crop leaves Our goal is to find and develop the more suitable deep learning methodologies for our task Therefore, we Proposed our system so we are using the Deep Learning in which the CNN (Convolutional neural network) is implemented to give more accurate results here we train the set of images dataset using deep learning and all the image processing will be done by CNN internally and we build the web application using the Django for GUI purpose where we provide the option of uploading the image if the user upload image it will processed by the Deep Learning and predict the results of the various crop diseases our application is more accurate and complete its work within less time it predicts correctly most of the time.
On the Effectiveness of Unified Debugging: An Extensive Study on 16 Program Repair Systems

Automated debugging techniques, including fault localization and program repair, have been studied for over a decade. However, the only existing connection between fault localization and program repair is that fault localization computes the potential buggy elements for program repair to patch. Recently, a pioneering work, ProFL, explored the idea of unified debugging to unify fault localization and program repair in the other direction for thefi rst time to boost both areas. More specifically, ProFL utilizes the patch execution results from one state-of-the-art repair system, PraPR, to help improve state-of-the-art fault localization. In this way, ProFL not only improves fault localization for manual repair, but also extends the application scope of automated repair to all possible bugs (not only the small ratio of bugs that can be automaticallyfi xed). However, ProFL only considers one APR system (i.e., PraPR), and it is not clear how other existing APR systems based on different designs contribute to unified debugging. In this work, we perform an extensive study of the unified-debugging approach on 16 state-of-the-art program repair systems for thefi rst time. Our experimental results on the widely studied Defects4J benchmark suite reveal various practical guidelines for unified debugging, such as (1) nearly all the studied 16 repair systems can positively contribute to unified debugging despite their varying repairing capabilities, (2) repair systems targeting multi-edit patches can bring extraneous noise into unified debugging, (3) repair systems with more executed/plausible patches tend to perform better for unified debugging, and (4) unified debugging effectiveness does not rely on the availability of correct patches in automated repair. Based on our results, we further propose an advanced unified debugging technique, UniDebug++, which can localize over 20% more bugs within Top-1 positions than state-of-the-art unified debugging technique, ProFL.
No Lean Season 2017 Pre-Analysis Plan

1. A replication of previous findings showing positive impact of incentivized migration on seasonal migration, caloric intake, food and non-food expenditure, income, and food security. Our aim is to estimate impact of a scaled version of the No Lean Season program: intensifying program implementation within branches and expanding the provision of loans to all eligible households. 2. Investigating the program’s spillover effects on workers at the migration destination who are not offered migration incentives. Given the scale of the No Lean Season program, we anticipate that there will be enough migration to noticeably affect destination labor markets. Destination workers include those who permanently reside at migration destinations as well as seasonal migrants from other areas. We aim to evaluate the effect of the program on these workers’ income and location choice.
Socket Capable Browser Plugins Result In Transparent Proxy Abuse

Transparent proxies allow organizations to influence and monitor the traffic from its users without their knowledge or participation. Transparent proxies act as intermediaries between a user and end destination, and aren't generally apparent to users sitting behind them. Enterprises, Hotels, and Internet Service Providers often use transparent proxy products to lower bandwidth consumption, speed up page loads for their users
Detection of Different Throw Types and Ball Velocity With IMUs and Machine Learning in Team Handball

The purpose of this study was to investigate if an inertial measurement unit (IMU) and machine learning could be used to detect different types of team handball throws and predict ball velocity. Throwing was measured using IMUs and a radar gun in seventeen participants during standing, running and jump throws with a circular and whip-like wind up. Using these data, machine learning could predict peak ball velocity with an error of 1.05 m/s and classify approach types and throw types with ~85–90% accuracy. It was concluded that to monitor throwing load, the combination of inertial measurement units and machine learning offers a practical and automated method of quantifying throw counts and discriminating throw types in handball players under standard conditions
Modal Estimation on a Warped Frequency Axis with Application to Coupled Piano String Modeling

Linear systems such as room acoustics and string oscillations can be modeled as the sum of a set of modes, each characterized by its frequency, damping and amplitude. Currently, the approaches for estimating mode parameters include spectral peak detection followed by energy envelope fitting, and optimization of system pole coefficients. In this paper, the mode frequencies and dampings are estimated directly from the generalized eigenvalues of Hankel matrices of system response samples, similar to ESPRIT. For greater resolution at low frequencies, such as required in audio applications, the estimation is done on a warped frequency axis. The frequencies and decay rates maybe further optimized, and mode amplitudes are fit using least squares. We use this method to model coupled piano strings where frequency warping captures the slightly mistuned triplets, and optimization captures the two-stage decay.
Rabbits and Study Habits : A Field Experiment on Pacesetters and Student Effort ∗

Many students perform below their academic potential due to a lack of study time. Targeting study time and evaluating the effects has thus far been challenging because of poor measurement of effort and the absence of information on students’ initial study plans. In a field experiment with 573 university students, I elicit detailed weekly study goals and plans from students and use these to construct individualized pacesetters (rabbits). Pacesetters are moving reference points that visualize the preferred study pace of the present self by moving exactly according to the initial study plan. I build a new educational technology to measure effort and to display the pacesetters to students in real time. Falling behind the pacesetter confronts the student with his or her procrastination. I find that students have more ambitious study goals when they set a pacesetter, but subsequently tend to fall behind quickly and are less likely to reach their goals. The pacesetter has no impact on study time, nor does it improve learning outcomes. I discuss treatment heterogeneity based on: gender, ability, and procrastination. JEL classification: I21, D91