Miracle-dz/UniFAR-FTUs huggingface dataset:
Antifreeze Proteins: Characteristics and Potential Applications

The freezing of water is usually fatal to most organisms because it causes extensive damage to cell membranes due to the formation of ice crystals. However, several structurally different classes of antifreeze proteins (AFPs) found in fish, insects, plants, and microorganisms, including bacteria, yeast, and fungi, have been found to be capable of modifying the growth of ice crystals by thermal hysteresis and ice recrystallization inhibition. This unique property could potentially be applied to medicine and the industry as it is useful when low-temperature storage is required and ice crystallization must be avoided. However, the application of AFPs today is not economically viable due to the complexity of the large proteins, the laborious procedures required, and the low yields obtained. A wide range of peptides mimicking their parent proteins were recently successfully designed and chemically synthesized. The developed approaches present new opportunities to understand the structure–function relationship of small-structured peptides with antifreeze properties. This mini-review highlights the diversity, classification, and properties of AFPs. The emerging applications of short mimetic peptides of AFPs and their potential application are also described.
Network Physical Address Based Encryption Technique Using Digital Logic

: We propose lightweight encryption technique called MOD-RC4 for 802.11. Lots of encryption techniques are developed for security of data packets in wireless networks. Security is major concern in wireless network. In this proposed technique, the source node encrypted the data packets using MAC address of wireless NIC card of destination node and sends to destination node by direct path or relay path. At destination node, first of all, MAC address of wireless NIC card is read automatically. Then convert it into binary form (This number is the secret key). Then generate the key stream using secret key and PRNG. Then the encrypted (cipher text) data will be converted by performing exclusive OR (XOR) operation using key stream. This process will produce original data (plain text data). ——————————  ——————————
Facial Expression Recognition Based on Multi-dataset Neural Network

Facial activity is the most powerful and natural means for understanding emotional expression for humans. Recent years, extensive efforts have been devoted to facial expression recognition by using neural networks. However, automated emotion recognition in the wild from facial images remains a challenging problem. In this paper, an effective facial expression recognition scheme is proposed. A multi-dataset neural network is developed to learn facial expression features in several different but related datasets. The novel multi-dataset network fuses the intermediate layers of a deep convolutional neural network (CNN) by using separate CNNs and a multi-dataset loss function. Experimental results performed on emotion database demonstrate that our proposed method outperforms state-of-the-art.
Security Challenges in Ghana, the Imperatives of States Security Agencies: A Study of the Ghana Police Service

Security is necessary for a stable democracy as well as flourishing development. Security challenges are prevalent in both developing as well as developed countries. However, a historical as well as recent security challenge in less developed countries suggests a rather interesting picture in comparison to developed countries. This study sought to unravel the security challenges in Ghana and the imperative of Ghana Police Service as a security agency. The mixed-method of data collection was used. The study established that, armed robbery, cybercrime and political vigilantism are the major security challenges in Ghana. It was revealed that, the inefficiency of the police is as results of political interference, lack of logistics, poor condition of service like accommodation, unfair treatment of junior officers among others. The insight gained led to the following recommendations: depoliticizing the police institution, upgrading their system to enhance effective communication, organization of periodic refresher courses among others.
The effects of feeding alfalfa pulp ensiled with wasted date (Phoenix dactylifera L.) on digestibility, microbial protein synthesis and ruminal fermentation characteristics in sheep.

Received: 12 Nov. 2019, Accepted: 09 Dec. 2019, Published online: 26 Dec. 2019. Abstract The aim of this study was to evaluate the effect of feeding alfalfa pulp ensiled with waste date (Phoenix dactylifera L.) on digestibility, microbial protein synthesis and ruminal fermentation characteristics in Kermani sheep. Alfalfa (Medicago sativa L.) pulps were ensiled with waste date (15% in dry matter) in buckets. After 45 days, chemical composition and pH of the silage were evaluated using four Kermani rams in a change-over design with four 21-day periods comprising of 16 days for adaptation and 5 days for sample collection. Treatments containing 4 diets: 1) control diet (without silage); 2) diet containing 10% silage; 3) diet containing 20% silage and 4) diet containing 30% silage. The results of this study showed that adding 15% waste date to alfalfa pulp during ensiling, improved silage quality and DM. The Flieg point and pH of silage were 94.26 and 3.8, respectively, with a total score quality evaluation of 19 that seemed to be a very good score. Nutrient digestibility, nitrogen (N) retention, blood parameters, urinary purine derivatives and microbial protein synthesis were not affected by treatments. The total population of Entodinium and total protozoa species were increased linearly with the increase in the level of alfalfa pulp ensiled with waste date in the diets. In conclusion, ensiling of alfalfa pulp with 15% waste date increased DM and silage quality and its feeding to sheep did not have negative effects on feed intake and nutrient digestibility. Due to the relatively low costs of alfalfa pulp and waste date, their inclusion in sheep diets can reduce the cost of feed and environmental pollution.
Business IT Alignment: A Never-ending Story

The impact of Information and Communication Technology (ICT) on organizations has been addressed extensively in research and practice. Leavitt and Whisler for example, observed as early as 1958 that Information Technology would soon spread (Leavitt and Whisler 1958). They stated: “One important reason for expecting fast changes in current practices is that information technology will make centralization much easier” (p. 43). In their view, modern information technology encroaches on one of the dilemmas that organizations grapple with, namely the impact of technology on how organizations act. It makes sense that the alignment of business with ICT, known in literature as business IT alignment (BITA), is a central issue for the management of organizations (see on this issue : Brancheau et al. 1996; Brancheau and Wetherbe 1987; Henderson and Venkatraman 1993; Herbert and Hartog 1986; Kappelman et al. 2014; Luftman et al. 2006; Nath 1989). In a longitudinal study started by Luftman in the nineties of the last century and continued by a.o. Kappelman (2014) it is shown that in the list of topmanagement concerns for IS/IT the BITA issue is in the top 3 since 1994. In table 1 the most recent overview of these top management concerns is shown.
Tracking Late Jurassic ornithopods in the Lusitanian Basin (Portugal): ichnotaxonomic implications

The Sociedade de História Natural in Torres Vedras, Portugal houses an extensive collection of as yet undescribed dinosaur tracks with ornithopod affinities. They have been collected from different Late Jurassic (Kimmeridgian–Tithonian) geological formations (Praia de Amoreira-Porto Novo, Alcobaça, Sobral, and Freixial) that outcrop along the Portuguese coast, and belong to two different sub-basins of the Lusitanian Basin (the Consolação and Turcifal sub-basins). Three main morphotypes can be distinguished on the basis of size, mesaxony and the morphology of the metatarsophalangeal pad impression. The minute to small-sized morphotype is similar to the Anomoepus-like tracks identified in other Late Jurassic areas. The small to medium-sized morphotype resembles the Late Jurassic–Early Cretaceous ichnotaxon Dinehichnus, already known in the Lusitanian Basin. Interestingly, these two morphotypes can be distinguished qualitatively (slightly different size, metatarsophalangeal pad impression and digit morphology) but are nevertheless difficult to discriminate by quantitatively analysing their length-width ratio and mesaxony. The third morphotype is considered a large ornithopod footprint belonging to the ichnofamily Iguanodontipodidae. This ichnofamily is typical for Cretaceous tracksites but the new material suggests that it might also be present in the Late Jurassic. The three morphotypes show a negative correlation between size and mesaxony, so the smaller tracks show the stronger mesaxony, and the larger ones weaker mesaxony. The Upper Jurassic ornithopod record from the Lusitanian Basin has yielded both small and medium-sized ornithopod remains, mainly iguanodontians such as dryosaurids and ankylopollexians, which are the main candidates to be the trackmakers.
Fuzzy based Risk Predictive Model for Cardiovascular Complication of Patient with Type 2 Diabetes Mellitus and Hypertension

Cardiovascular diseases are chronic diseases that cause serious morbidity and mortality worldwide. Unfortunately, the patients with type 2 diabetes mellitus and hypertension have a high risk of having a cardiovascular complication. For these reasons, patients with type 2 diabetes mellitus and hypertension should be aware of cardiovascular complication along their healthcare journey. To prevent cardiovascular complication from diabetes and hypertension, accurate risk prediction is required for a long term self-management process. Consequently, this paper proposes a fuzzy logic based method for predicting cardiovascular risk particularly for a patient with type 2 diabetes mellitus and hypertension. This paper also proposes a set of factors based on the patient’s lifestyle as the key factors besides clinical factors because of their implicit impact on the quality of life of the patient. The proposed model thus employs 15 predictors for both clinical and lifestyle risk factors. Additionally, the proposed model is constructed based on the scientific data and implicit knowledge of the experts. The experiment with 121 patients shows that the proposed prediction model provides 96.69% accuracy compared to those decided by the experts.
Analyzing the Role of Trade Openness in Economic Growth of Pakistan

Trade openness is a vivid indicator of emerging economies & one of the most important determinants of growth. Therefore, quite a number of researchers have endeavored to analyze the significance & impact of trade openness on economic growth for various economies. Generally, the theoretical framework supports the constructive & positive impact of economic openness of a country for its overall economic development; however, there are mixed outcomes of empirical findings, especially for developing countries that experience fluctuations in their economic growth rate. This research work has employed trade to GDP ratio as a proxy variable for trade openness to examine its effect on the growth of Pakistan. The finding of this study does not reveal any considerable effect of trade liberalization during 1972-2016 on the growth of the Pakistan economy. The study concludes its premise based on empirical results that those economies that have a comparative advantage in trade with significant competitiveness usually benefit from liberalization, export promoting, and diversifying policies. The trading partners of Pakistan were and are mostly Western countries that have the comparative advantage of trade over Pakistan. Therefore, the government of Pakistan needs to promote & diversify its exports to those countries in which Pakistan has a comparative advantage in the international market.
Impact of maximal power training with and without plyometric on speed endurance and upper body power of team handball players

Purpose: The aim of this research is to investigate the impact of maximal power training with and without plyometrics on speed endurance and upper body power of team handball players. Material: Sixty college level men team handball players were randomly selected from Coimbatore district as subjects. Their age ranged between 18 and 25 years. The selected subjects were divided into three equal groups consisting of twenty each. No attempt was made to equate the groups. Experimental group I (n = 20) underwent maximal power training with plyometrics (MPTWP), Experimental group II (n = 20) underwent maximal power training without plyometrics (MPTWOP) for a period of 12 weeks and group III (n = 20) acted as control group (CG), the subjects in control group were not engaged in any training programme other than their regular work. Data obtained were evaluated in SPSS package. Results: The F value revealed that the speed endurance and upper body power were significantly improved due to the influence of maximal power training with plyometrics. Conclusions: As a result, 12 weeks of maximal power training with plyometrics can be said to increase the speed endurance and upper body power of team handball players.
SCREENING OF THREE SOLANACEAE PLANT VARIETIES TO MELOIDOGYNE INCOGNITA INFECTION WITH REFERENCE TO NEMATODE ABUNDANCE IN IRAQ

A nematological survey was conducted at the rhizosphere of Solanaceae plants the growing seasons of 2017-2018 that represented different fields in five counties of Iraq state i.e., Alsaniyha, Shamiyah, Ghamas, Shaafa’i and Sudair. Alsaniyah area recorded the highest rate of root nematode infection (105.88%), followed by Al-Shamiya area (70.0%), while Al-Sudair came in last one (27.58%). Meloidogyne assumed to be the key pest of vegetable crops in the five surveyed counties. Solanaceae cultivars were affected by nematode infection at various degrees. Among tested two tomato cultivars, cv. Ahlam accomplished the highest reduction of the tested parameters while the eggplant cultivar, Long purple stated the highest reduction percentage and pepper cv California Wonder showed the highest reduction percentage for the same plant growth criteria as well.
Effects of Acacia decurrens Willd. tree-based farming system on soil quality in Guder watershed, North Western highlands of Ethiopia

Abstract Continuous conversion of land for different agricultural production purposes has resulted in degradation of soil resources. Rehabilitating soil quality through sustainable land management is one of the most pressing agenda in agriculture. Hence, this study was conducted to evaluate the trends of major soil quality after the introduction of A. decurrens tree-based farming in Guder watershed. Soil samples were collected from 5 land use types, 2 soil depths, and 3 slope positions with 3 replications and then analysed for selected soil physicochemical quality indicators. Selected soil physicochemical indicators were subjected to three-way ANOVA. The result revealed that the highest clay particles and soil bulk density were recorded at A. decurrens tree farmland and cropland soils, respectively. The maximum soil pH was recorded from natural forest (5.99), subsurface soil layer (5.56) and lower slope (5.57). The lowest soil organic carbon and total nitrogen contents were observed in cropland. Greater available phosphorus (13.58) mg kg−1 was obtained in the topsoil depth of A. decurrens tree farmland at the lower slope. Among the studied soil quality indicators total nitrogen, cation exchange capacity and soil pH were strongly and positively correlated with soil organic carbon. The finding of this study showed that shifting of cereal based into A. decurrens tree-based farming by smallholder farmers can improve the fertility and health of soils and then boost crop productivity. Therefore, the right integration of A. decurrens tree in the farming system can be an alternative approach to reverse soil quality deterioration in degraded agricultural landscapes of Ethiopia.
Corporate investment, financing and payout decisions under financial constraints and uncertainty: Evidence from UK firms

We investigate interactions among corporate investment, financing, and payout decisions under uncertainty, using a panel of UK-listed firms. We model these corporate decisions within a simultaneous equations system where we treat each decision as endogenous, but allow for their contemporaneous interdependence, as implied by the flow-of-funds framework. We find that the effect of uncertainty on corporate investment is positive and significant, while those on debt financing and dividend payouts are significant and negative. Accordingly, firms facing greater uncertainty appear to increase investment, by resorting to internal finance and by cutting dividends rather than resort to external finance by issuing new debt. Further, we divide the entire sample into two groups, namely financially more constrained firms and less constrained firms, in order to explore the sensitivity of our results to financial constraints. We find that the simultaneity among the three corporate decisions is more pronounced for financially more constrained firms, but the effect of uncertainty is more significant for firms which are financially less constrained. It appears that financial constrains are the possible channel through which corporate decisions are jointed determined. Overall, our results offer new insight into the complex interdependence of corporate behaviour by UK-listed firms, under financial constraints and uncertainty.
Machine Learning Based Sentiment Analysis on Twitter Data

: With the increase of social networking epoch and its growth, the net has become one in all the powerful platforms for online learning, exchanging ideas and sharing opinions. Social media contain an enormous amount of the info for sentiment analysis within the type of tweets, blogs, and updates on the status, posts, etc.This paper addresses the matter of sentiment analysis in twitter; that's classifying tweets in keeping with the sentiment into positive, negative or neutral. Analysing the emotions of the general public became important to seek out the reviews of the shoppers for any product within the market, predicting political elections and predicting socio economic phenomena like stock market. The aim of this project is to develop a functional classifier for accurate and automatic sentiment classification of an unknown tweet stream by using convolutional neural networks.
Foliage Orientation and Carbon Gain in Two Tussock Grasses as Assessed with a New Whole-plant Gas Exchange Model

The effect of foliage orientation on light interception and photosynthesis within two tussock grasses, Agropyron desertorum and Pseudoroegneria spicata, was assessed with a new three-dimensional simulation model. The model can account for spatial differences in foliage distribution within the tussock as well as differences in physiological properties of the foliage elements. Light interception and net photosynthesis are calculated for sunlit and shaded foliage. Model predictions of whole-plant net photosynthesis (A tuss ), transpiration (E tuss ), water-use efficiency, expressed as the ratio A tuss to E tuss , and average intercellular CO 2 compared very well with measurements in the field taken with a whole-plant gas-exchange system (.)
Formalization of Functional Requirements and Their Traceability in UML Diagrams—A Z Notation Based Approach

- In this paper, we propose an approach for formalizing the “Functional Requirements” section of a SRS document and establish traceability of these requirements among different UML diagrams that are used in requirement analysis and design phases after formally representing them, using Z notation, which is a non-executable, but, a strongly typed specification language. We represent the “formalized” functional requirements with their traceability among different UML diagrams visually using E-R Diagram. Development of a tool based on this approach will produce a visual representation of formalized functional requirements and their traceability among different formalized UML diagrams, from which automated traceability of requirement in different phases of software development can be achieved. This tool will enable us with a solution that will be formal and hence automatically verifiable, at the same time understandable by both the developers and users.
High-throughput genomic analysis of virulence and resistance mechanisms among microbial pathogens

The rapid development of high-throughput sequencing technologies poses to transform many aspects of human health. It is without question that within the next decade the ability to rapidly sequence any infection to determine the genetic structure of the etiologic agent will be feasible. To effectively utilize such an approach we must first develop a greater understanding of the genetic variation of clonal microbial pathogens as well as the functional significance of the variation found. To this extent I have focused on three projects. i. ) By sequencing 36 community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) from within a defined geographical area we are able to understand how the genome is evolving overtime. Sequence analysis of the strains suggests the population is under diversifying selection for genes related in virulence. In addition, mutational burden of individual isolates correlates with the severity of infection suggesting the CA-MRSA is evolving away from it's hyper-virulent ancestor to become less pathogenic. ii. ) Acquiring resistance to the gram-positive antimicrobial daptomycin has previously been shown to be a complicated process that can be achieved through multiple routes. I describe the non-linear multi-allelic acquisition of resistance in a laboratory evolved strain of Bacillus subtilis. Through the use of allelic replacement and transcriptomic analysis three loci (dctP/ ybdI, yvrG, yqeG) are shown to be involved in the resistance phenotype through the alteration of cell wall and cell membrane metabolism pathways. iii. ) Finally, I present methods to acquire rare sequences from complex pools of DNA. I demonstrate two such methods, microdroplet PCR and RNA/DNA hybridization to accomplish this. I apply these methods to the capturing of Plasmodium vivax from dried whole blood spots thus alleviating the need to leukocyte filtration. I discuss future application for the integrating all three studies towards the use of clinical sequencing for the detection and monitoring of infectious diseases