Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-modal Dependency Tree for Video Captioning

Generating ﬂuent and relevant language to describe visual content is critical for the video captioning task. Many existing methods generate captions using sequence models that predict words in a left-to-right order. In this paper, we investigate a graph structured model by explicitly modeling the hierarchical structure in the sentences to further improve the ﬂuency and relevance of the generated captions. To this end, we propose a novel video captioning method that generates a sentence by ﬁrst constructing a multi-modal dependency tree and then traversing the constructed tree, where the syntactic structure and semantic relationship in the sentence are represented by the tree topology. To take full advantage of the information from both vision and language, both the visual and textual representation features are encoded into each tree node. Different from existing dependency parsing methods that generate uni-modal dependency trees for language understanding, our method constructs multi-modal dependency trees for language generation of videos. We also propose a tree-structured reinforcement learning algorithm to effectively optimize the captioning model, where a novel reward is designed by evaluating the semantic consistency between the generated sub-trees and the ground-truth tree. Extensive experiments on several video captioning datasets demonstrate the effectiveness of the proposed method.
Use of mobile agent in E-commerce

In today's world, more and more stress in given to information and its access. And with this more emphasis is given to the mobility of information. This trend has led to evolution of electronic commerce which is acting as a promising way the business is conducted. Computer systems have evolved from centralized system to client server paradigm then to mobile agent paradigm. Mobile agent systems consist of agent and hosts which provide working environment to the agents. Mobile agent consists of program code and execution state and when agent is dispatched to some other host both are transferred. They travel to different trading sites and locate the most befitting deal, negotiate the deal and even finalize them on behalf of their owners. This paper reviews the working of mobile agents in field
The effects of host sincerity on tourists’ perceived destination image

ABSTRACT This study aims to explore the effects of host sincerity on tourists’ perceived destination image, satisfaction, and behavioral intentions. Data were collected via an on-site survey in China and analyzed using structural equation modeling analysis. The findings suggest that local hosts should show their sincerity toward tourists in tourist-host interactions to create a positive destination image and trigger positive behavioral intentions of tourists for sustainable development of the travel destination. Residents can be active partners and co-producers of destination branding. This study highlights interactions between tourists and local residents as important attributes of the destination experience.
Analysis of CO2 Emission Reduction Effect of On-Site Production Precast Concrete Member according to Factory Production Environment

Precast concrete (PC) method of construction is preferred for excellence in the reduction of construction period, lightweight, and durability and for PC member to be mostly transported to a site after its production in the in-plant production because the in situ production of the PC member is negatively perceived because of the limitation of space or production process being complex and difficult. However, if the PC member is produced on site and installed, it is possible to reduce the carbon dioxide emissions that are generated during shipping and loading and unloading, which are indirectly required for in-plant production. Carbon dioxide emission reduction effect due to the difference between the in situ production and in-plant production process of the PC member was confirmed by the existing studies, but the study of the carbon dioxide reduction effect according to various production environments of the in-plant production has not been performed. Therefore, the purpose of this study is to analyze the CO2 emission reduction effect of the PC member produced in site according to the in-plant production environment. As a result, it was found that when PC members were produced on site, there was an effect of reducing CO2 emissions by an average of 25.64% compared to factory production. In future, the results of this study will be used as basic data for establishing a CO2 emission reduction plan at construction sites.
Muscarinic signaling regulates voltage‐gated potassium channel KCNQ2 phosphorylation in the nucleus accumbens via protein kinase C for aversive learning

The nucleus accumbens (NAc) plays critical roles in emotional behaviors, including aversive learning. Aversive stimuli such as an electric foot shock increase acetylcholine (ACh) in the NAc, and muscarinic signaling appears to increase neuronal excitability and aversive learning. Muscarinic signaling inhibits the voltage‐dependent potassium KCNQ current which regulates neuronal excitability, but the regulatory mechanism has not been fully elucidated. Phosphorylation of KCNQ2 at threonine 217 (T217) and its inhibitory effect on channel activity were predicted. However, whether and how muscarinic signaling phosphorylates KCNQ2 in vivo remains unclear. Here, we found that PKC directly phosphorylated KCNQ2 at T217 in vitro. Carbachol and a muscarinic M1 receptor (M1R) agonist facilitated KCNQ2 phosphorylation at T217 in NAc/striatum slices in a PKC‐dependent manner. Systemic administration of the cholinesterase inhibitor donepezil, which is commonly used to treat dementia, and electric foot shock to mice induced the phosphorylation of KCNQ2 at T217 in the NAc, whereas phosphorylation was suppressed by an M1R antagonist. Conditional deletion of Kcnq2 in the NAc enhanced electric foot shock induced aversive learning. Our findings indicate that muscarinic signaling induces the phosphorylation of KCNQ2 at T217 via PKC activation for aversive learning.
A novel compact-size branch-line coupler

A novel compact-size branch-line coupler without any implementation of lumped-elements, bonding wires, and via holes is proposed. In this study, the size of the proposed coupler occupied only 45% of the conventional branch-line coupler at 2.4GHz. The performances of the circuit can be competed with the conventional coupler. The element sizes of this coupler can be realized easily by using simply standard printed-circuit-board etching processes. It is very useful for applications in the wireless communication systems.
Respect for Human Rights after the End of the Cold War

By directly affecting democratization, globalization, domestic conflict, and interstate conflict, the end of the Cold War was hypothesized to exert an indirect effect on the propensity of governments to respect the human rights of their citizens. The findings for a sample of 79 countries showed that torture, disappearances, and extrajudicial killings continued at about the same rate even after the Cold War ended. However, after the end of the Cold War, there was significant improvement in government respect for the right against political imprisonment. Contrary to expectations, it was found that governments that decreased their involvement in interstate conflict or experienced decreased domestic conflict did not tend to increase respect for the right against political imprisonment. As hypothesized, it was found that governments that became more democratic or increased their participation in the global economy after the end of the Cold War tended to manifest higher levels of respect for the right of their citizens not to be politically imprisoned. However, a closer look at several recent examples of democratization in Africa suggests that any human rights improvements resulting from post-Cold War democratization may be short-lived. In the cases examined, improved government respect for the right against political imprisonment resulted from short-term manipulations by the leaders of `illiberal' or `demonstration' democracies who were not committed to democratization or to the advancement of the human rights of their citizens.
Job Satisfaction and Implication for Employee’s Performance in Nigerian Public Sector

The study sought to determine the factors responsible for job satisfaction of an employee, assess the relationship between job satisfaction and employee commitment, ascertain the extent to which public sector organizations motivate their workers. The study had population of 452 in which a sample size of 212 was derived using Taro Yaman’s Formula. Instrument used for data collection was primarily questionnaire. The descriptive survey research design was adopted for the study. The hypotheses were tested using Pearson chi-square and Pearson product moment correlation coefficient statistical tools. The findings indicated that Work itself, advancement and promotion are basic factors responsible for job satisfaction of an employee (X 2c = 210.016 > X 2 t = 9.49; p < 0.05). There was a positive relationship between job satisfaction and employee commitment (r = .893, p< .05). Public sector organizations significantly motivate their workers (X 2 c= 28.772 > X 2t = 9.49: p < 0.050). The study concluded that motivation is the force that energizes, direct and sustains a person’s effort towards the achievement of a goal. The study recommended that oorganizations should ensure that workers are promoted on time and at when due, so as increase employees job satisfaction and organizational commitment.
An architecture for information specification based on an SME enterprise model

This paper describes a CASE tool architecture for a manufacturing information specification. The objective of this is to establish a new approach to the specification of information requirements for an SME IT system. An enterprise model for an SME metalworking company is introduced and mapped onto the ARIS architecture, this enables the modelling tool to be described in the context of enterprise modelling, which highlights the important relationship between enterprise models and information specification.
Restoration of MiR-34a Expression by 5-Azacytidine Augments Alimta -Induced Cell Death in Non-Small Lung Cancer Cells by Downregulation of HMG B1, A2 and Bcl-2 Pathway

Objective Alimta (Pemetrexed) as an antifolate drug has been approved for the treatment of lung cancer. The aim of the present study was to investigate the combination effect of 5-Azacytidine (5-aza) and Alimta on the miR-34a and its target genes expression and induction of apoptotic cell death in non-small lung cancer A549 cells. Materials and Methods In this experimental study, lung cancer A549 cells were treated with various concentrations of Alimta alone and combined with 5-Aza. Then, viability was assessed by trypan blue and MTT assays. mRNA expressions were performed by real time-polymerase chain reaction (PCR) and western blot. Flow cytometry used to detect apoptotic/ necrotic cells and cell cycle arrest. Results Alimta alone reduced viability of the cells in a dose dependent manner with the half-maximal inhibitory concentration (IC50) value of 12 µM. Pretreatment of the cells with 5-aza (5 µM) induced a synergistic cytotoxic effect with IC50of 3 µM. Sequential exposure of the cells to 5-aza and Alimta enhanced miR-34a expression and significantly downregulated HMGB1, HMGA2 and BCL-2 expressions. Also, it was associated with reduction of nuclear HMGB1 and HMGA2 content. Caspase-3 activation, HMGB1 release into extracellular space and staining of the cells with annexine V/PI suggested that 5-aza reduced late apoptotic/necrotic cell death induced by Alimta. In addition, combination of 5-aza and Alimta arrested the cells at S and sub-G1 phases and inhibited colony formation. Conclusion 5-aza synergistically enhances Alimta induced apoptotic cell death through HMG proteins regulation, MIR34A gene expression and intrinsic apoptosis mechanism, providing a promising combination therapy in clinical lung cancer therapy.
S1473550421000252jra 359..376

Interstellar travel in the Milky Way is commonly thought to be a long and dangerous enterprise, but are all galaxies so hazardous? I introduce the concept of galactic traversability to address this question. Stellar populations are one factor in traversability, with higher stellar densities and velocity dispersions aiding rapid spread across a galaxy. The interstellar medium (ISM) is another factor, as gas, dust grains and cosmic rays all pose hazards to starfarers. I review the current understanding of these components in different types of galaxies, and conclude that red quiescent galaxies without star formation have favourable traversability. Compact elliptical galaxies and globular clusters could be ‘super-traversable’, because stars are packed tightly together and there are minimal ISM hazards. Overall, if the ISM is the major hindrance to interstellar travel, galactic traversability increases with cosmic time as gas fractions and star formation decline. Traversability is a consideration in extragalactic surveys for the Search for Extraterrestrial Intelligence (SETI).
TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness

Adversarial Transferability is an intriguing property - adversarial perturbation crafted against one model is also effective against another model, while these models are from different model families or training processes. To better protect ML systems against adversarial attacks, several questions are raised: what are the sufficient conditions for adversarial transferability and how to bound it? Is there a way to reduce the adversarial transferability in order to improve the robustness of an ensemble ML model? To answer these questions, in this work we first theoretically analyze and outline sufficient conditions for adversarial transferability between models; then propose a practical algorithm to reduce the transferability between base models within an ensemble to improve its robustness. Our theoretical analysis shows that only promoting the orthogonality between gradients of base models is not enough to ensure low transferability; in the meantime, the model smoothness is an important factor to control the transferability. We also provide the lower and upper bounds of adversarial transferability under certain conditions. Inspired by our theoretical analysis, we propose an effective Transferability Reduced Smooth(TRS) ensemble training strategy to train a robust ensemble with low transferability by enforcing both gradient orthogonality and model smoothness between base models. We conduct extensive experiments on TRS and compare with 6 state-of-the-art ensemble baselines against 8 whitebox attacks on different datasets, demonstrating that the proposed TRS outperforms all baselines significantly.
rsudp: A Python package for real-time seismic monitoring with Raspberry Shake instruments

The uses of low-cost seismographs in science and education are becoming more widely known as these devices become more popular (Anthony et al., 2018; Diaz et al., 2020; Lecocq et al., 2020; Subedi et al., 2020; Walter et al., 2019; Winter et al., 2021). Raspberry Shake seismographs are commonly used in schools, by Shake community members, and other individuals having no formal training in seismology. The existence of this class of instruments highlighted the need for easy-to-use visualization and notification software to complement these devices. Because all Raspberry Shake instruments are able to forward data as user datagram protocol (UDP) packets, taking the opportunity to exploit the existence of this streaming data was obvious.
Experiments in real-time spatial data acquisition for obstacle detection

Rapid spatial data collection is desirable for many applications in engineering and construction. Recent technology developments such as Flash LADAR devices (Laser Detection and Ranging) allow rapid acquisition of range and intensity scene data. Methods that process the ouput into 3D side models and display or provide the location of objects on a site signif icantly improve work processes. A particularly useful application is modeling the presence of obstacles in structured or unstructured construction-type scenes including people, material, and equipment. The development of obstacle avoidance systems improves safety during the operation of equipment and efficiency for pick ing and plac ing objects. This paper describes laboratory experiments and field trials under realistic conditions for the development of obstacle detection algorithms for construction machinery using a high frame -rate Flash LADAR sensor. The focus is on the acquisition of experimental data to determine the benefits and limitations of this approach within the construction industry. Tests were conducted to analyze and discuss the sensor performa nce and evaluate the trade -off between sce ne detail and processing speed. Future research goals are in the development of algorithms allowing accurate scene modeling by acquir ing data from a moving object and detecting both stationary and moving obstacles in the motion path.
Yet a Better Closed-Form Formula for the 3D Nearest Rotation Matrix Problem

This communication complements the results recently presented in [1] showing that they can be extended to deﬁne an efﬁcient and robust method to determine the rotation matrix nearest to an arbitrary 3 × 3 matrix. This problem arises in different areas of robotics that range from the simple case in which we have to restore the orthogonality of a noisy rotation matrix to point-cloud registration or hand-eye calibration. We show that the new method compares favorably with the classical approaches to address this problem and also with more recent methods [2, 3]
Spatial Domain Segmentation Algorithm for Tumour Detection and Wavelet Based Texture Analysis

The most challenging and complex area of research in biomedical image processing is segmentation and analysis of brain tumour. It is proved by Statistics that amongst various brain ailments, brain tumour is may be fatal if it will be carcinogenic. The paper proposes a spatial domain segmentation algorithm for detection of brain tumour using multiple images of brain MR and k-means algorithm. Also a Brain Tumour Texture Analysis algorithm is proposed that uses fractal dimension, fractal area, and wavelet to classify type of texture present in brain tumour. The results obtained by those algorithms are found to be highly satisfactory and verified for ground truth by medical practitioners. The proposed algorithms were compared with other state-of-the-art algorithms and found to be better in terms of accuracy, precision and recall.
Servant Leadership Relationship to Emotional Demands, Stress, and Well-Being of the Leader

Previous studies have investigated the outcomes of servant leadership on the followers and organization. The present study investigated the outcomes of practicing servant leadership on the leader by identifying the relationships between servant leadership and emotional demand, stress, and well-being. Eighty-seven leaders completed a survey on their leadership behaviors, emotional labor, emotional intelligence, stress, and well-being. Two servant leadership scores were used to analyze the relationships. Multiple correlation analyses, linear regressions, and hierarchical multiple regressions were conducted and found partial support across all hypotheses. Overall trending patterns indicated servant leadership had a positive correlation with emotional labor, emotional intelligence, and stress, and a negative correlation with well-being. Results also indicated that emotional labor mediated the relationship between servant leadership and emotional intelligence, and between servant leadership and well-being. Servant leadership is beneficial to the organization, but can be negative to the leader’s health if suggested considerations are not incorporated. SERVANT LEADERSHIP OUTCOMES 2 MONTCLAIR STATE UNIVERSITY Servant Leadership Relationship to Emotional Demands, Stress, and Well-Being of the Leader
Machine Learning for Prediction of Noise Pollution

: Noise pollution is a developing problem now a days. The quickest effect is an illness of human mental health. Now days sleep disorder is a serious cause. Continuous propagation of noise can create frustration. Noise can make a more contribution to cardiovascular effect in human beings. That is a reason it is very difficult to live a healthy life for all. This system work on the methods of Internet of Things (IOT) which is an evolving technology. It also check the live intensity of noise in a particular area and also maintain a log over the internet, for further analysis and prediction. This system sensing the presence of polluted noise range. A micro controller is use to process the noise data and generate reports for authorities to keep a watch and take some precaution over the excessive noise. It also classify the noise using machine learning algorithm. This system can be used in various areas. It can be use near schools, college campus, hospital and no honking area and traffic areas.
EFFICACY OF DIFFERENT BOTANICALS FOR THE MANAGEMENT OF RHYZOPERTHA DOMINICA (FABRICIUS) IN STORED SORGHUM

An experiment was conducted to investigate the insecticidal activity of different grain protectants viz., red chilli fruit powder, Capsicum annuumL. 5.0, black pepper seed powder, Piper nigram L. 0.5, neem seed kernel powder, Azadirachta indica A. Juss 5.0, neem leaf powder, A. indica 5.0, turmeric rhizome powder, Curcuma longa L. 5.0, tulsi leaf powder, Oscimum basilicum L. 5.0 per cent (w/w) and Untreated (control) against Rhyzopertha dominica (Fabricius) in stored sorghum. The result revealed that blac k pepper seed powder 0.5 per cent exhibited maximum adult mortality 65.00 and 29.75 per cent after 48 hrs release of adults at 4 and 60 DAT, respectively. The next effective treatment was red chilli frui t 5.0 and neem seed 5.0 per cent. The germination of sorghum grains was found to be above 80 per cent with neem leaf, tulsi leaf and turmeric rhizome powder while neem seed kernel, red chiili fruit and black pepper seed powder showed somewhat detrimental to the germination up to 60 days of storage.
Effect of Plant- Based ParabenFree Venusia Max Cream on Skin Hydration in HealthyIndividuals with Dry Skin

Hydration in Healthy Individuals with Dry Skin. J Clin Investigat Dermatol. 2021;9(2): 4 Effect of PlantBased Paraben Free Venusia Max Cream on Skin Hydration in Healthy Individuals with Dry Skin Monil YN Gala1*, Snehal Sameer M1, Sujeet Narayan C1, Rahul Rathod R1, Mane A1, Pandit S1, Alok Ranjan S2 and Anup Avijit C2 1Department of Medical Affairs, Dr Reddy’s Laboratories, India 2Department of FR and D, Dr Reddy’s Laboratories, India
Soil fertility amendment using cocoa pod husk and plantain peels powders for Okra ( Abelmoschus esculentus , kirikou variety) production in Dschang (Cameroon Western Highlands)

plantain peels, rice husk, palm kernel cake wastes, potato peels, amongst others are abundantly generated in large quantities and often abandoned in field sites, littered in the surrounding, constituting foul odors, breeding grounds for pathogenic micro-organisms and environmental pollutants. These huge, cheap, unused organic wastes are an excellent source of humus and can be recycled for use as bio fertilizers considering the growing deficiency of plant nutrients in crop fields, high cost and low efficiency of synthetic fertilizers. Compost and biochar technologies are often expensive and involve a lot of technicalities for the local farmer to understand. Nevertheless, many findings [11,12] have shown success of simple techniques such as incorporation of organic wastes into the soil. Simeon and Ambah carried out amendments under controlled conditions like greenhouses, screen house, which do not reflect the farmers’ field conditions, hence, farmers’ adoptions of such research results are often limited [13]. Although several studies have been carried out on the