Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing the Interactions Between the Cytoplasmic Domains of Arabidopsis BRI1 and BAK1.

ROBINSON, JEFFREY LEE. Characterizing the Interactions Between the Cytoplasmic Domains of Arabidopsis BRI1 and BAK1 (Under the direction of Dr. Michael B. Goshe). Brassinosteroid-insensitive 1 (BRI1) and BRI1-associated kinase 1 (BAK1) are leucine rich repeat receptor like kinases (LRR RLKs) in plants that have been shown to play a role in development, controlling factors such as plant growth and male fertility. They are known to dimerize and upon activation, their signal transduction pathway is initiated. Although a lot of research has been done on BRI1 and BAK1 in recent history, the binding sites of the two proteins have not been identified. Chemical crosslinking has become an important tool in characterizing and refining protein structure. Chemical crosslinking allows for the examination of the “faces” of proteins that are close in space in the tertiary structure but may be distant in sequence or on a different protein. Chemical crosslinking-mass spectrometry (CXL-MS), when used alongside other structure determining techniques such as X-ray crystallography or NMR, is becoming more prevalently used in discovering how proteins oligomerize. Once basic protein structure is found via crystallography, CXL-MS can be used to determine the linking areas of each protein. Some protein complexes can be difficult to crystalize to study by crystallography or resonance assignments made by NMR may not be able to identify protein domains that bind one another. CXL-MS can be used to help identify the linking areas in proteins. The cytoplasmic domains of BRI1 and BAK1 were analyzed using CXL-MS in an attempt to identify the binding residues between the two. Surface plasmon resonance (SPR) is a commonly used technique to study protein interactions. SPR is an optical phenomenon that stems from the reflection of plane polarized light at an interface between a metal film and liquid phase. It allows for the measurement of association and dissociation rates of two proteins, and their binding affinities in real time. Analytical ultracentrifugation is another technique that can identify binding kinetics by subjecting the proteins in solution to a gravitational field. The association and dissociation rates of LRR RLKs have not been widely researched to date. The goal of studying the binding kinetics of two proteins is to be able to determine the concentrations of the complexed and un-complexed forms throughout a reaction based on initial conditions and binding constants. This information can be helpful when performing crosslinking experiments to provide better reaction conditions. To this end, the binding kinetics of BRI1 and BAK1 cytoplasmic domains were analyzed using SPR and AUC.
All-Fiber Vector Bending Sensor Based on a Multicore Fiber With Asymmetric Air-Hole Structure

In this article we present an all-fiber vector bend sensor by means of a self-fabricated micro-structured multicore optical fiber. The reported solution is based on differential intensity variations of the light transmitted along the cores whose changes are influenced by the bending angle and orientation. The unique asymmetric structure of the air-holes in the optical fiber provides each core with different confinement losses of the fundamental mode depending on the bending radius and orientation, making each of the cores bend-sensitive in a range of at least 80°. It has been experimentally demonstrated that the reported sensor enables the bending angle and orientation to be detected in a full range of 360° without any dead-zones, and the possibility of end point detection with millimeter precision. Additionally, a reconstruction of the bending vector has been carried out theoretically, and a good match can be observed between the experimental and theoretical data.
ÖZELLİK SEÇİMİ İLE BİRLEŞTİRİLMİŞ DESTEK VEKTÖR MAKİNELERİNİ KULLANARAK KÖMÜRÜN ÜST ISIL DEĞERİNİN KISA VE ELEMENTEL ANALİZ DEĞİŞKENLERİNDEN TAHMİNİ

The gross calorific value (GCV) is an essential thermal property of coal which indicates the amount of heat energy that could be released by burning a specific quantity. The primary objective of the presented study is to develop new GCV prediction models using support vector machines (SVMs) combined with feature selection algorithm. For this purpose, the feature selector RReliefF is applied to the dataset consisting of proximate and ultimate analysis variables to determine the importance of each predictor of GCV. In this way, seven different hybrid input sets (data models) were constructed. The prediction performance of models was computed by using the square of multiple correlation coefficient (R 2 ), root mean square error (RMSE), and mean absolute percentage error (MAPE). Considering all the results obtained from this study, the predictor variables moisture (M) and ash (A) obtained from the proximate analysis and carbon (C), hydrogen (H) and sulfur (S) obtained from the ultimate analysis were found to be the most relevant variables in predicting GCV of coal, while the predictor variables volatile matter from the proximate analysis and nitrogen from the ultimate analysis did not have a positive effect on the prediction accuracy. The SVM-based model using the predictor variables M, A, C, H, and S yielded the highest R 2 and the lowest RMSE and MAPE with 0.998, 0.22 MJ/kg, and 0.66%, respectively. For comparison purposes, multilayer perceptron and radial basis function network were also used to predict GCV.
The impact of board size on board demographic faultlines

Purpose Demographic faultlines are associated with negative group processes and low performance. Little is known about the formation of faultlines in boards and how they can be weakened to capitalize on the positive effects of diversity. Design/methodology/approach This study draws on social identity theory and faultlines theory to provide insights into how gender and age faultlines are formed in a board. Subsequently, it proposes and tests a U-shaped board size–faultlines strength relationship. Archival data were collected on 288 organizations listed on the Australian Securities Exchange. Findings Hierarchical regression analyses indicate that small- and large-sized boards experience stronger faultlines than medium-sized boards. Originality/value This study provides pioneering evidence for a U-shaped relationship between board size and demographic faultlines strength. These findings inform practice by suggesting an optimal board size.
Transformasi praktik akuntansi Usaha Mikro, Kecil, Menengah (UMKM): dari memori ke catatan

Research on the accounting practices of micro, small and medium enterprises (SMEs) in Indonesia shows the failed implementation of accounting standards by SMEs. Since accounting practice is determined by internal and external factors that surround it and small firm is a unique entity, this research finding is interesting to be studied further by understanding accounting practiced by SMEs. Accounting may practice in the other form that further explains the "low" of SMEs accounting practice. This study uses transcendental phenomenology to understand SMEs accounting practice. Informant of this research is the owner of SMEs manufacturing business. Manufacturing enterprises are selected with consideration of the complexity of the business leading to a greater need for accounting practices. The results show the existence of an evolution of accounting practices. Accounting after tasks delegation was practiced in the note prior to practiced in the memories. Task delegation is the motivation for accounting practice evolution and fairness is value contained.
Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations

Riming is an efficient process of converting liquid cloud water into ice and plays an important role in the formation of precipitation in cold clouds. Due to the rapid increase in ice particle mass, riming enhances the particle’s terminal velocity, which can be detected by ground-based vertically pointing cloud radars if the effect of vertical air motions can be sufficiently mitigated. In our study, we first revisit a previously published approach to relate the radar mean Doppler velocity (MDV) to rime mass fraction (FR) using a large ground-based in situ dataset. This relation is then applied to multiyear datasets of cloud radar observations collected at four European sites covering polluted central European, clean maritime, and Arctic climatic conditions. We find that riming occurs in 1%–8% of the nonconvective ice containing clouds with median FR between 0.5 and 0.6. Both the frequency of riming and FR reveal relatively small variations for different seasons. In contrast to previous studies, which suggested enhanced riming for clean environments, our statistics indicate the opposite; however, the differences between the locations are overall small. We find a very strong relation between the frequency of riming and temperature. While riming is rare at temperatures lower than −12°C, it strongly increases toward 0°C. Previous studies found a very similar temperature dependence for the amount and droplet size of supercooled liquid water, which might be closely connected to the riming signature found in this study. In contrast to riming frequency, we find almost no temperature dependence for FR.
Ensemble Adaboost classifier for accurate and fast detection of botnet attacks in connected vehicles

The key characteristic of smart cities (ie, connectivity and intelligence) has enabled connected vehicles to work together to accomplish complex jobs that they are unable to perform individually. Connectivity not only being an inevitable blessing but also poses growing cybersecurity challenges for connected vehicles. The overall risk of connected vehicles is wide as the cybercriminals are nowadays applying versatile approaches (botnets, phishing, zero‐days, rootkits, etc) to disrupt their communication. The botnet, capable of launching distributed denial of service attack, is a potential threat for any connected ecosystem due to its excessive capabilities of using maximum compromised devices. Hence, the detection of botnet attacks has become a pinnacle point for cybersecurity analysts. Existing studies lack in detecting botnet at the earliest and accurately. This article presents an approach to detect the botnet attacks at an early stage and accurately utilizing typical network traffic and temporal features. The proposed approach use machine learning algorithms for the detection of botnet attack(s) and present a detailed comparison of the decision tree, probabilistic neural network, sequential minimal optimization, and Adaboost classifiers, as well as comparison of the proposed approach with existing studies in this domain, is also done. Furthermore, it investigates the role of temporal features for botnet detection. The proposed approach accomplishes the promising true positive rate of 99.7%. Results show that our methodology is efficient compared with the existing studies.
The Relationship between Participation Funds and Macroeconomic Variables: SVAR Analysis Approach

Participation banks are in the same financial environment with the conventional banks, so the macro-economic variables are expected to affect the participation funds. The purpose of this study is to examine the relationship between participation funds and macroeconomic variables for Turkey. The relation between the total Turkish currency funds in participation banks and macroeconomic variables is examined using the weekly data series from 10th of July 2015 to 5th of November 2018 by applying VAR and SVAR analysis. The total amount of the deposits of participation banks, weighted average interest rates, Borsa Istanbul gold prices, deposit interest rates of conventional banks, M2 defined money supply and total foreign exchange reserves of Central Bank of the Turkish Republic and USD exchange rate data were used as the secondary data tools. As a result of the VAR analysis, it was found that the total deposits of Islamic banks are primarily affected by money supply and the quarterly deposit interest rates of conventional banks. The SVAR analysis on the basis of these variables reveals that there is a positive correlation between money supply and participation funds while the relation is negative with the quarterly deposit interest rates of conventional banks and the participation funds. According to these analyses, participation funds benefit from the expansionary monetary policy, however; the interest rate policy of conventional banks negatively affects the fund inflow of the Islamic banks.
A paradoxical perspective on technology renewal in digital transformation

To realize their strategic goals and maintain a competitive advantage in the digital era, organizations must periodically renew their digital platforms and infrastructures. However, knowledge about such technology renewal is scattered across diverse research streams, so insights into the process are both limited and fragmented. In this article, we consolidate insights from previous research to conceptualize technology renewal as an inherently paradoxical digital transformation process that requires organizations to simultaneously remove their technological foundation and build on the practices that depend on it to implement a new technological foundation. Previous research suggests that technology renewal initiatives are driven by three paradoxical tensions: (a) established vs renewed technology usage, (b) deliberate vs emergent renewal practices and (c) inner vs outer renewal contexts. We apply this framing to a longitudinal case study in which we analyse and explain how an organization's responses to manifestations of these tensions eventually led to a vicious cycle of continued investments into two overlapping and largely incompatible digital platforms over a 9‐year period. Based on these conceptual and empirical insights, we theorize technology renewal as a paradoxical, and increasingly critical, digital transformation process that forces managers to make decisions in complex and ambiguous choice situations.
Comparative study of corrosion resistance between four non-commercial high manganese steel models and 9% nickel steel in aqueous solution of H2SO4

Abstract The present study aims to establish a comparison of corrosion resistance between four (non-commercial) high manganese steel models in relation to 9% nickel steel in an aqueous solution of H2SO4. High manganese steels have emerged as an alternative material for the manufacture of equipment for the storage and transportation of liquefied petroleum gas due to their mechanical properties and mainly for the lower cost compared to 9% nickel steel. The electrochemical techniques used were open circuit potential, linear polarization and electrochemical impedance spectroscopy. The results obtained by these techniques have helped to understand the phenomena that produce a lower corrosion resistance of high manganese steels when compared to 9% nickel steel in aqueous solutions.
Migratory routes and wintering locations of declining inland North American Common Terns

ABSTRACT Common Terns (Sterna hirundo) breeding at inland lakes in North America have experienced significant population declines since the 1960s. Although management actions aimed at mitigating effects of habitat loss and predation have been largely effective, numbers continue to decline, which suggests that the population may be limited during the nonbreeding season. Between 2013 and 2015, we used light-level geolocators to track Common Terns nesting at 5 inland colonies—from Lake Winnipeg in Manitoba, Canada, to the eastern Great Lakes region of the United States and Canada—to identify migratory routes and stopover and wintering sites and to determine the strength of migratory connectivity among colonies. Within 46 recovered tracks, we found evidence of a longitudinal gradient in use of migration routes and stopover sites among colonies and identified major staging areas in the lower Great Lakes and at inland and coastal locations along the Atlantic coast, Florida, and the Gulf of Mexico. Low migratory connectivity across inland colonies illustrates high intermixing within wintering sites, with many birds spending the nonbreeding season in Peru (70%) and the remainder spread throughout the Gulf of Mexico, Central America, and northwestern South America. While the large spatial spread and intermixing of individuals during the nonbreeding season may buffer local effects of climate change and human disturbance, the aggregation of individuals along the coast of Peru could make them vulnerable to events or changes within this region, such as increased frequency and intensity of storms in the Pacific, that are predicted to negatively influence breeding productivity and survival of Common Terns. Identifying sources of mortality during the nonbreeding season, quantifying winter site fidelity, and reinforcing the importance of continued management of inland breeding colonies are vital priorities for effective conservation and management of this vulnerable population.
The effect of alcohol withdrawal syndrome severity on sleep, brain and cognition

Abstract In alcohol use disorder, drinking cessation is frequently associated with an alcohol withdrawal syndrome. Early in abstinence (within the first 2 months after drinking cessation), when patients do not exhibit physical signs of alcohol withdrawal syndrome anymore (such as nausea, tremor or anxiety), studies report various brain, sleep and cognitive alterations, highly heterogeneous from one patient to another. While the acute neurotoxicity of alcohol withdrawal syndrome is well-known, its contribution to structural brain alterations, sleep disturbances and neuropsychological deficits observed early in abstinence has never been investigated and is addressed in this study. We included 54 alcohol use disorder patients early in abstinence (from 4 to 21 days of sobriety) and 50 healthy controls. When acute physical signs of alcohol withdrawal syndrome were no longer present, patients performed a detailed neuropsychological assessment, a T1-weighted MRI and a polysomnography for a subgroup of patients. According to the severity of the clinical symptoms collected during the acute withdrawal period, patients were subsequently classified as mild alcohol withdrawal syndrome (mild-AWS) patients (Cushman score ≤ 4, no benzodiazepine prescription, N = 17) or moderate alcohol withdrawal syndrome (moderate-AWS) patients (Cushman score > 4, benzodiazepine prescription, N = 37). Patients with severe withdrawal complications (delirium tremens or seizures) were not included. Mild-AWS patients presented similar grey matter volume and sleep quality as healthy controls, but lower processing speed and episodic memory performance. Compared to healthy controls, moderate-AWS patients presented non-rapid eye movement sleep alterations, widespread grey matter shrinkage and lower performance for all the cognitive domains assessed (processing speed, short-term memory, executive functions and episodic memory). Moderate-AWS patients presented a lower percentage of slow-wave sleep, grey matter atrophy in fronto-insular and thalamus/hypothalamus regions, and lower short-term memory and executive performance than mild-AWS patients. Mediation analyses revealed both direct and indirect (via fronto-insular and thalamus/hypothalamus atrophy) relationships between poor sleep quality and cognitive performance. Alcohol withdrawal syndrome severity, which reflects neurotoxic hyperglutamatergic activity, should be considered as a critical factor for the development of non-rapid eye movement sleep alterations, fronto-insular atrophy and executive impairments in recently detoxified alcohol use disorder patients. The glutamatergic activity is involved in sleep-wake circuits and may thus contribute to molecular mechanisms underlying alcohol-related brain damage, resulting in cognitive deficits. Alcohol withdrawal syndrome severity and sleep quality deserve special attention for a better understanding and treatment of brain and cognitive alterations observed early in abstinence, and ultimately for more efficient relapse prevention strategies.
Bioactive Healing Abutment as a Potential Tool for the Treatment of Peri-Implant Disease—In Vitro Study

The common use of dental implants for dental reconstruction poses new treatment challenges for physicians, peri-implantitis being a particularly difficult one. Micro-organisms, including drug-resistant Staphylococcus spp. strains, play a crucial role in the etiology of peri-implantitis. In this paper, the authors assess the efficacy of a bioactive healing abutment (BHA) of their own design for the local release of antibiotics as a potential tool for the treatment of peri-implant disease. BHA filled with a collagen material, combined with the antibiotics clindamycin and tetracycline, was tested in vitro by disk diffusion assay. Antibacterial activity was observed for the chosen Staphylococcus aureus and Staphylococcus epidermidis bacterial strains. In addition, the impact of titanium discs (which were used to make the BHA) was monitored. The results show that the zone diameter breakpoints for BHA are higher than those of standard absorbent paper discs in both tested strains for both tested antibiotics. This work demonstrates that the proposed BHA can serve as an effective and precise drug carrier. The release of antibiotics from the described implant device is easy to control and allows for an effective local antibacterial in vitro treatment. The procedure is inexpensive, easy to perform, and repeatable.
Vascular ATP‐sensitive K+ channels support maximal aerobic capacity and critical speed via convective and diffusive O2 transport

Oral sulphonylureas, widely prescribed for diabetes, inhibit pancreatic ATP‐sensitive K+ (KATP) channels to increase insulin release. However, KATP channels are also located within vascular (endothelium and smooth muscle) and muscle (cardiac and skeletal) tissue. We evaluated left ventricular function at rest, maximal aerobic capacity ( V̇ O2max) and submaximal exercise tolerance (i.e. speed–duration relationship) during treadmill running in rats, before and after systemic KATP channel inhibition via glibenclamide. Glibenclamide impaired critical speed proportionally more than V̇ O2max but did not alter resting cardiac output. Vascular KATP channel function (topical glibenclamide superfused onto hindlimb skeletal muscle) resolved a decreased blood flow and interstitial PO2 during twitch contractions reflecting impaired O2 delivery‐to‐utilization matching. Our findings demonstrate that systemic KATP channel inhibition reduces V̇ O2max and critical speed during treadmill running in rats due, in part, to impaired convective and diffusive O2 delivery, and thus V̇ O2, especially within fast‐twitch oxidative skeletal muscle.