Miracle-dz/UniFAR-FTUs huggingface dataset:
DNA/protein binding, DNA cleavage, cytotoxicity, superoxide radical scavenging and molecular docking studies of copper(II) complexes containing N-benzyl-N′-aryl-N′′-benzoylguanidine ligands

Five copper(II) complexes containing N,N′,N′′-trisubstituted guanidine ligands were synthesized and characterized by elemental analyses and UV-Visible, FT-IR, EPR and mass spectroscopic techniques. The synthesized copper(II) complexes (1–5) bear the general formula [Cu{C6H5CONC(NR)NHCH2C6H5}2] where R = phenyl (1), 4-methylphenyl (2), 4-ethoxyphenyl (3), 2-methoxyphenyl (4) or 1-naphthyl (5). The four coordinated square planar geometry of the complexes was confirmed by the single crystal X-ray diffraction study. The interaction of the Cu(II) complexes with calf thymus DNA (CT DNA) was explored using absorption and fluorescence spectroscopic methods. The results revealed that the complexes have an affinity constant for DNA in the order of 104 M−1 and the mode of interaction is non-covalent intercalation. The DNA cleavage study showed that the complexes cleaved DNA without any external agent. The interaction of Cu(II) complexes with bovine serum albumin (BSA) was also studied using absorption and fluorescence techniques. The cytotoxic activity of the Cu(II) complexes was probed in vitro against human breast (MCF7) and lung (A549) cancer cell lines. The complexes were also tested against mouse embryonic fibroblast (NIH 3T3) cell lines. Complexes 1 and 3 have good cytotoxic activity which is comparable with the cyclophosphamide drug. The complexes were less cytotoxic towards normal cell lines showing that they affect only cancer cell lines. Superoxide radical scavenging property of the complexes was assessed using the NBT assay. Copper(II) complexes showed appreciable superoxide radical scavenging activity with IC50 values ranging from 1.53 to 5.62 μM. A further molecular docking technique was employed to understand the binding of the complexes toward the molecular target DNA and human DNA topoisomerase I.
Bodeum: Encouraging Working Parents to Provide Emotional Support for Stay-at-Home Parents in Korea

Although gender equality is commonly found globally, many countries in Asia still show stereotypical gender roles within family relationships between fathers and mothers. In those countries, most stay-at-home mothers are mainly responsible for childcare and housework while fathers work so that some stay-at-home mothers are highly stressed by single childcare. To relieve their parenting stress, emotional support from their spouse is an important factor. However, working parents in single-income families tend to underestimate the childcare difficulties of their spouses. In this work, we propose Bodeum, a proof-of-concept mobile system to facilitate spousal communication by sharing stay-at-home parent's stress level, their childcare activities, and their baby's status with working parents to encourage emotional support for stay-at-home parents. A 2-week feasibility study with nine families in South Korea suggests that Bodeum enhanced spousal communication about parenting stress and showed potential for parenting mothers to lower their perceived parenting stress.
ANTIMICROBIAL EFFECT OF GOLD AND SILVER NANOPARTICLES ON MDR E. COLI AND MOLECULAR DETECTION OF AMINOGLYCOSIDE MODIFYING ENZYMES–PRODUCING MDR E. COLI ISOLATED FROM UTI PATIENT

This study was reached in laboratories of Biology Department in Faculty of Science. It describes the antimicrobial effect of gold and silver nanoparticles on resistance of antibiotics bacterial species that isolated from urinary tract infection patients in the province of Najaf. A total number of 120 samples were assembled from patients with UTI admitted to AL-Sader Teaching Hospital, AL-Hakim General Hospital and AL-Furat Alawsat Hospital in AL-Najaf Governorate. The results proved the antibacterial activities of some resistance antibiotics involved Amoxicillin-clavulanic acid, Ceftriaxone, Nitrofurantoin, Cefotaxime, Ciprofloxacin and Trimethprim +Sulamethoxazole which increased in the attendance of gold with silver nanoparticles and these antibiotic together causing the inhibition of E. coli isolates growth and meaningfully compared with the presence of silver nanoparticles alone as well as more than the case of the presence of gold nanoparticles alone with these antibiotic. The results presented that the aac(6')-Ib was considered the most common types of phosphotransferase (APHs) was detected in E. coli isolates, 19 (98.3%) were have aac(6')-Ib gene and 4 (20%) were have aph(3')-IIa gene, while the aac(3')-I and aac(3)-III genes were not detected in any E. coli isolates.
PriSEC: A Privacy Settings Enforcement Controller

Online privacy settings aim to provide users with control over their data. However, in their current state, they suffer from usability and reachability issues. The recent push towards automatically analyzing privacy notices has not ac-companied a similar effort for the more critical case of privacy settings. So far, the best efforts targeted the special case of making opt-out pages more reachable. In this work, we present PriSEC, a Privacy Settings Enforcement Controller that leverages machine learning techniques towards a new paradigm for automatically enforcing web privacy controls. PriSEC goes beyond ﬁnding the webpages with privacy settings to discovering ﬁne-grained options, presenting them in a searchable, centralized interface, and – most importantly – enforcing them on-demand with minimal user intervention. We overcome the open nature of web development through novel algorithms that leverage the invariant behavior and rendering of webpages. We evaluate the performance of PriSEC to ﬁnd that it precisely annotates the privacy controls for 94.3% of the control pages in our evaluation set. To demonstrate the usability of PriSEC, we conduct a user study with 148 participants. We show an average reduction of 3.75x in the time taken to adjust privacy settings compared to the baseline system.
Strategic Macroprudential Policymaking: When Does Cooperation Pay Off?

I study whether emerging economies can navigate the global financial cycle more successfully by resorting to internationally coordinated macroprudential regulations. For this, I set an open economy model with banking frictions in a center-periphery environment with multiple emerging economies. Then, I evaluate the performance of several policy arrangements that differ by the degree and type of cooperation. I find that cooperation is not always beneficial relative to nationally-oriented policies. Instead, only schemes where the financial center acts cooperatively generate welfare gains. Two mechanisms generate the gains: a cancellation effect of national incentives to manipulate the global interest rate and a policy motive under cooperation (with a center) for steering larger investment flows to emerging economies. The first mechanism eliminates unnecessary movements in the policy instruments, and the second helps prevent capital retrenchments in the financial center. Finally, the shortrun dynamics show these mechanisms lead to smoother and conservative policy responses that allow for a better performance of the peripheries after external shocks, while generating improved leverage dynamics that favor the global economic recovery. These results make a case for cooperation as a way to mitigate the potential adverse effects of excessive fluctuations in the macroprudential instruments. JEL Codes: F38, F42, E44, G18
Sustainable management of freshwater swamp forest as an ecotourism destination in Indonesia: a system dynamics modeling

As a freshwater swamp forest that still remains in Java, the existence of Rawa Danau as an ecotourism destination is important to be explored, because its utilization is not yet based on sustainable management principles. For this reason, a system dynamics modeling was then made that integrates various factors in the biophysical, social, and economic dimensions to obtain the best alternative for managing the future ecotourism destinations. Management alternatives are designed in three scenarios: deep ecotourism oriented to very strong/strong sustainability; shallow ecotourism oriented to weak sustainability; and mass tourism oriented to very weak sustainability. The results showed that deep ecotourism was the most suitable scenario to be implemented. Through this scenario, the control of several parameters that were successfully carried out during the 10 years of the simulation are as follows: 1) restrain the growth rate of tourist numbers so as not to burden the environment; 2) reforesting almost all forest land converted so that the restoration of forest functions goes well; 3) increase local community income so that the community gets adequate economic benefits; 4) increase environmental investment so that stakeholders benefit economically, ecologically, and socially in an integrated manner; 5) maintaining biodiversity at a high level; 6) maintain swamp water reserves at a very good level; 7) reduce the volume of solid waste so that it does not burden the environment.
NestiNg Biology of URBAN CoopeR’s HAwks

In recent decades Cooper’s Hawks have successfully colonized urban landscapes, where there may be ample prey but also a greater prevalence of disease in their prey. We searched for nesting Cooper’s Hawks in and around Berkeley, California, from 2002 to 2010, locating 95 nests, 89 of which successfully fledged at least one nestling. On average, each nest produced 3.6 fledglings. We evaluated the possible effects of the protozoan parasite Trichomonas gallinae on Cooper’s Hawk reproduction from the proportion of potential prey items brought to Lindsay Wildlife Experience that tested positive for the parasitic disease. We did not find a correlation between T. gallinae in potential prey species and nest success (i.e., if the nest fledged any offspring) or reproductive success (i.e., number of fledglings produced). Similarly, we did not find a relationship between reproductive success and distance to parks or percent of impervious surface within 500 m of the nest. The high reported rates of reproduction and high densities of Cooper’s Hawk in Berkeley and neighboring Albany suggest a robust population, and we did not find evidence that T. gallinae influences its reproductive success. The Cooper’s Hawk (Accipiter cooperii) is a common woodland hawk that often focuses on birds as prey (Rosenfield et al. 2019b). While it nests throughout the United States and boreal Canada in a variety of tree species in dense woods (Rosenfield et al. 2019b), in recent decades it has adapted to urban habitats (Boal and Mannan 1998). Cooper’s Hawks in more urban environments differ in behavior and nesting habitats (Mannan and Boal 2000, Estes and Mannan 2003, Stout et al. 2007, Chiang et al. 2012, Millsap 2018). In southern California, for example, rural Cooper’s Hawks typically use oak and riparian woodland, whereas their urban counterparts use parks and ornamental plantings (Chiang et al. 2012). Urban pairs are also more tolerant of human approaches to the nest and are bolder than their nonurban counterparts (Boal and Mannan 1999). Urban habitats may not be productive or self-sustaining for Cooper’s Hawks, acting as population sinks, which rely on immigration to maintain stable populations (Reynolds 1983, Bosakowski et al. 1993). However, some urban environments may actually confer advantages on the hawk populations, such as increased prey populations (Millsap 2018). In contrast, Mannan et al. (2008) and Boal et al. (1998) found negative effects of urbanization in Tucson, Arizona, which may function as a population sink for Cooper’s Hawks, where populations need to be replenished by immigration from outside populations. Specifically, in doves, the primary prey of urban Cooper’s Hawks in Tucson, they found a high prevalence of disease caused by
Spousal Health Shocks and Physical Activity among Older Adults

Using the 2004-2014 data from Health and Retirement Study, we examined the impact of spousal health shocks (i.e., new diagnosed medical conditions and functional limitations) on older adults’ physical activity (PA). In particular, we explored whether individuals learn from their spouses’ health shocks and adjust their PA. Using fixed-effect two-stage models, we found individuals, especially males and the less educated, increased their PA levels in response to their spousal health shocks directly and indirectly (through the negative impact of spousal health shocks on their own self-reported health). This finding suggests potential beneficial effects of providing health promoting information to both spouses when one spouse develops health problems.
What Determines Heterogeneous Merger Effects on Competitive Outcomes?*

We examine whether heterogeneous mergers effects predominantly stem from technological or product market heterogeneities. Using detailed firmand product-specific information, we employ a heterogeneous merger effects model. Our results show that merging firms realize substantial heterogeneous post-merger effects on competitive outcomes such as production or prices. Merger effects vary substantially across merging firms, depending on the firms’ pre-merger efficiency levels, price elasticities, and innovative activities. Firms’ efficiency level and price elasticities prior to merging determine large post-merger heterogeneities. The results show that product market attributes (differences in inefficiencies and price elasticities) cause larger postmerger heterogeneities compared with technology market attributes.
Demand Composition and the Strength of Recoveries

We argue that recoveries from demand-driven recessions with expenditure cuts concentrated in services or non-durables will tend to be weaker than recoveries from recessions more biased towards durables. Intuitively, the smaller the bias towards more durable goods, the less the recovery is buffeted by pent-up demand. We show that, in a standard multi-sector business-cycle model, this prediction holds if and only if, following an aggregate demand shock to all categories of spending (e.g., a monetary shock), expenditure on more durable goods reverts back faster. This testable condition receives ample support in U.S. data. We then use (i) a semi-structural shift-share and (ii) a structural model to quantify this effect of varying demand composition on recovery dynamics, and find it to be large. We also discuss implications for optimal stabilization policy.
Learning to Select the Best Forecasting Tasks for Clinical Outcome Prediction

The paradigm of ‘pretraining’ from a set of relevant auxiliary tasks and then ‘ﬁnetuning’ on a target task has been successfully applied in many different domains. However, when the auxiliary tasks are abundant, with complex relationships to the target task, using domain knowledge or searching over all possible pretraining setups is inefﬁcient and suboptimal. To address this challenge, we propose a method to automatically select from a large set of auxiliary tasks, which yields a representation most useful to the target task. In particular, we develop an efﬁcient algorithm that uses automatic auxiliary task selection within a nested-loop meta-learning process. We have applied this algorithm to the task of clinical outcome predictions in electronic medical records, learning from a large number of self-supervised tasks related to forecasting patient trajectories. Experiments on a real clinical dataset demonstrate the superior predictive performance of our method compared to direct supervised learning, naive pretraining and simple multitask learning, in particular in low-data scenarios when the primary task has very few examples. With detailed ablation analysis, we further show that the selection rules are interpretable and able to generalize to unseen target tasks with new data.
A Lightweight Collaborative Deep Neural Network for the Mobile Web in Edge Cloud

Enabling deep learning technology on the mobile web can improve the user’s experience for achieving web artificial intelligence in various fields. However, heavy DNN models and limited computing resources of the mobile web are now unable to support executing computationally intensive DNNs when deploying in a cloud computing platform. With the help of promising edge computing, we propose a lightweight collaborative deep neural network for the mobile web, named LcDNN, which contributes to three aspects: (1) We design a composite collaborative DNN that reduces the model size, accelerates inference, and reduces mobile energy cost by executing a lightweight binary neural network (BNN) branch on the mobile web. (2) We provide a jointly training method for LcDNN and implement an energy-efficient inference library for executing the BNN branch on the mobile web. (3) To further promote the resource utilization of the edge cloud, we develop a DRL-based online scheduling scheme to obtain an optimal allocation for LcDNN. The experimental results show that LcDNN outperforms existing approaches for reducing the model size by about 16x to 29x. It also reduces the end-to-end latency and mobile energy cost with acceptable accuracy and improves the throughput and resource utilization of the edge cloud.
Twine: A Unified Cluster Management System for Shared Infrastructure

We present Twine, Facebook’s cluster management system which has been running in production for the past decade. Twine has helped convert our infrastructure from a collection of siloed pools of customized machines dedicated to individual workloads, into a large-scale shared infrastructure with fungible hardware. Our goal of ubiquitous shared infrastructure leads us to some decisions counter to common practices. For instance, rather than deploying an isolated control plane per cluster, Twine scales a single control plane to manage one million machines across all data centers in a geographic region and transparently move jobs across clusters. Twine accommodates workload-specific customization in shared infrastructure, and this approach further departs from common practices. The TaskControl API allows an application to collaborate with Twine to handle container lifecycle events, e.g., restarting a ZooKeeper deployment’s followers first and its leader last during a rolling upgrade. Host profiles capture hardware and OS settings that workloads can tune to improve performance and reliability; Twine dynamically allocates machines to workloads and switches host profiles accordingly. Finally, going against the conventional wisdom of prioritizing stacking workloads on big machines to increase utilization, we universally deploy power-efficient small machines outfit with a single CPU and 64GB RAM to achieve higher performance per watt, and we leverage autoscaling to improve machine utilization. We describe the design of Twine and share our experience in migrating Facebook’s workloads onto shared infrastructure.
PREPARATION AND IDENTIFICATION OF NEW DERIVATIVE OF ACETAMINOPHEN AND STUDY ITS APPLICATION IN THE DETERMINATION OF CU (II) USING SPECTROPHOTOMETRIC METHOD

This paper includes the preparation and diagnosis of the new organic reagent for acetaminophen by available spectral methods such as infrared spectroscopy, ultraviolet-visual radiation, C.H. N elements and H1NMR techniques. New derivative used in a simple and sensitive spectrophotometric methods for the determination of copper(II) ion is based on the complex formation by new reagent in acid medium which shows maximum absorbance at 504nm. Under the optimum experimental conditions such as the pH of the medium, reagent concentration, reagent volume, addition order, time effect and temperature. At the best conditions, the copper (II) quantitatively be determined in the range of (0.05-10) mg/l, The limit of detection (LOD)and limit of quantification (LOQ) were found to be 0. 0353μg/ml and 0. 1176μg/ml, respectively and Sandal sensitivity is 0.025 μg. cm, The percentage recovery of the drug and preparation samples for the proposed method ranged from 100-102.3%.
How soil carbon accounting can improve to support investment-oriented actions promoting soil carbon storage

Enhancing soil health can improve agricultural productivity and soil organic carbon (SOC) sequestration. The United Nations Framework Convention on Climate Change’s (UNFCCC) Koronivia Joint Work on Agriculture, Sustainable Development Goal (SDG) 15 and the Land Degradation Neutrality Framework demonstrate the increasing attention of policymakers to the importance of SOC for land productivity and food security. In addition, the 4 per 1000 Initiative has been promoting a global partnership to facilitate multiple stakeholders to encourage action at all levels to increase SOC stocks globally.
BigFuzz: Efficient Fuzz Testing for Data Analytics Using Framework Abstraction

As big data analytics become increasingly popular, data-intensive scalable computing (DISC) systems help address the scalability issue of handling large data. However, automated testing for such data-centric applications is challenging, because data is often incomplete, continuously evolving, and hard to know a priori. Fuzz testing has been proven to be highly effective in other domains such as security; however, it is nontrivial to apply such traditional fuzzing to big data analytics directly for three reasons: (1) the long latency of DISC systems prohibits the applicability of fuzzing: naïve fuzzing would spend 98% of the time in setting up a test environment; (2) conventional branch coverage is unlikely to scale to DISC applications because most binary code comes from the framework implementation such as Apache Spark; and (3) random bit or byte level mutations can hardly generate meaningful data, which fails to reveal real-world application bugs. We propose a novel coverage-guided fuzz testing tool for big data analytics, called BigFuzz. The key essence of our approach is that: (a) we focus on exercising application logic as opposed to increasing framework code coverage by abstracting the DISC framework using specifications. BigFuzz performs automated source to source transformations to construct an equivalent DISC application suitable for fast test generation, and (b) we design schema-aware data mutation operators based on our in-depth study of DISC application error types. BigFuzz speeds up the fuzzing time by 78 to 1477X compared to random fuzzing, improves application code coverage by 20% to 271%, and achieves 33% to 157% improvement in detecting application errors. When compared to the state of the art that uses symbolic execution to test big data analytics, BigFuzz is applicable to twice more programs and can find 81% more bugs.
The evolution of travel recommender systems: A comprehensive review

Travel has always been innate desire of human beings. People wanted to travel irrespective of any hurdles like geographical barrier, age, gender, or colour with different motivations. Nowadays travel and adventure became the most trending entertainment as well. Planning a trip is a time-consuming and herculean task for inexperienced travelers. Here comes the possibility of expert opinion for scheduling a perfect travel plan. With the development of information technology and social media, there are numerous possibilities and opportunities in fetching suitable information which can turn out to set up an appropriate travel plan and hence enhance the quality of travel. The signiﬁcance of a Recommender System (RS) comes in the picture which can address travel-related queries. Personalized Travel RS will add more customization and user-speciﬁc features than Automatic Travel RS. In this paper, we conducted a detailed review and chronological evolutions of various methods and techniques used in the travel and tourism sector and compared their efﬁciency in Recommendations.