Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Product Search Tools for Online Consumers with Little Product Knowledge: Clustering Versus Faceted Search

This study compares and contrasts different types of search tools—clustering search, rich-faceted search, and less-faceted search—in terms of their performance in online shopping product searches. In the experiment, two groups of people, a music-expert group and a computer-expert group, conducted searches for two different products (one for a novice search and the other for an expert search). Search performance was measured on three different shopping search websites—Clusty Shopping, PriceGrabber, and Yahoo Shopping. In addition, the participants’ perceptions of each website’s usefulness, directability/controllability, and their likelihood of future use are measured through their subjective ratings in questionnaires. The results of this research provide insight into how online consumers with different levels of product knowledge experience different types of search tools, with regard to search performance, perceived usefulness and controllability, and website preference.
Investigating the Type of Gene Action Conditioning Tolerance to Aluminum (Al) Toxicity in Tropical Maize

Maize is a third important cereal crop in the world after wheat and rice. In Zambia, it is an important staple crop. Its production is however hampered by both biotic and abiotic factors. Among the abiotic factors, Aluminum (Al) toxicity causes high yield losses and is directly linked to acidic soils. Application of lime can ameliorate this problem, but it is expensive for small scale farmers. Developing maize varieties that are tolerant to Al toxicity is cheaper and feasible for small scale farmers. The purpose of this research was to investigate the type of gene action conditioning tolerance to aluminum toxicity in tropical maize. Eleven inbred lines were mated in an 8 male (4 moderately tolerant and 4 susceptible) x 3 female (resistant) North Carolina Design II. Results revealed that general combining ability (GCA) effects due to both males and females were highly significant (P≤ 0.001) for root biomass. The shoot length GCA effects due to both male and female respectively were significant (P≤ 0.01). Similarly, the GCA effects due to females and males for root length were significant, P≤ 0.01 and P≤ 0.05 respectively. The genotype CML 511 had the most desirable significant GCA effect value (1.40) for root length among the male lines while CML 538 had the most desirable significant GCA effect value (0.92) among the female lines. The baker’s ratio for root length was found to be 0.49 implying that both additive and non-additive gene action were important in conditioning aluminum toxicity tolerance in tropical maize.
Дискусійні питання діагностики та лікування сепсису у вагітних і породіль у світлі настанови Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock (2016)

Физиологические особенности беременных имеют свои особенности котрые вносят свои коррективы в классическую картину диагностики и лечения сепсиса/септического шока в даной категории больных. Целью этой работы было изучить особенности сепсиса и септического шока в беременных и рожениц учитывая проколол Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock:2016. Проблема сепсиса актуальна в том числе и в акушерстве. В настоящее время инфекции занимают третье место в структуре материнской летальности и составляют около 15%. В статтье обсуждаются результаты диагностики и лечения 14 беременных/рожениц с сепсисом, котрый возник вследствии перитонита как следствия хориманионита и после родового эндометрита. Больные поступали в клинику в 2101-2016 г. Всем больным было проведено интенсивную терапию (воле-мическая ресусцитация, кардио-респираторная поддержка, антибактериальная терапия) и операциооное вмешательство (ликвидация перитонита, санация и дренирование брюшной полости). Состояние болных было оценено в 14,5±1,5 балы за шкалой АРАСНЕ 11, а состояние полиорганной дисфункции в – 5,0±1 бал за шкалой SOFA.
How broadly do product preannouncement performance effects generalize? Product life cycle and switching cost perspectives

Firms use preannouncements to inform customers about the impending introduction of a new product or service. These preannouncements are significant events because they provide customers with product specific information while signaling the health, strategic intent, and future of a company. One important area of research in this field investigates the performance consequences of product preannouncements (PPA). However, a notable gap in our knowledge exists, because the focus of past research has been on studying wealth effects rather narrowly in certain industries, e.g., high-tech, or under certain contingencies. This restrictive approach is surprising, because PPA are observed in a broad range of product categories. Moreover, product life cycle and consumer switching cost theories predict performance effects of PPA irrespective of category or context. The author addresses this lack of generalizability by using switching cost and life cycle theories to hypothesize positive performance effects of PPA independent of context and contingencies. The event study method from finance is used to empirically test the relationship between PPA and stock prices in a broad sample of events comprising multiple product categories. Using events reported in the Wall Street Journal, evidence of a positive effect of PPA on stock prices irrespective of the type of product or context involved is found. Several managerial implications of the study are noted and avenues for further research are outlined.
Rate Analysis of Uplink Massive MIMO With Low-Resolution ADCs and ZF Detectors Over Rician Fading Channels

In order to increase energy efficiency (EE), analog-to-digital converters (ADCs) with a low resolution are used to reduce the internal power consumption in massive multiple-input multiple-output (MIMO) systems. In this letter, we derive the uplink spectral efficiency (SE) of massive MIMO systems with low-resolution ADCs over Rician fading channels and using zero-forcing (ZF) detectors. To obtain a closed-form expression of the sum rate, we adopt the additive quantization noise model (AQNM), where the quantization noise is treated as an additive and independent noise. Our analysis is supported by various numerical results. For instance, compared with Rayleigh fading, specific conditions under Rician fading are needed to keep a good tradeoff between EE and system performance while using low-resolution ADCs.
Ad hoc network security and modeling with stochastic petri nets

AD HOC NETWORK SECURITY AND MODELING WITH STOCHASTIC PETRI NETS by Congzhe Zhang Advances in wireless technology and portable computing along with demands for high user mobility have provided a major promotion toward the development of ad hoc networks. These networks feature dynamic topology, self-organization, limited bandwidth and battery power of a node. Unlike the existing commercial wireless systems and fixed infrastructure networks, they do not rely on specialized routers for path discovery and traffic routing. Security is an important issue in such networks. Typically, mobile nodes are significantly more susceptible to physical attacks than their wired counterparts. This research intends to investigate the ad hoc network routing security by proposing a performance enhanced Secure ad hoc On-demand Routing protocol (SOR). Specifically, it presents a method to embed "Security Level" into ad hoc on-demand routing protocols using node-disjoint multipath, and to use "maximum hopcount" to restrict the number of routing packets in a specific area. The proposed scheme enables the use of security as a marked factor to improve the relevance of the routes discovered by ad hoc routing protocols. It provides customizable security to the flow of routing protocol messages. In general, SOR offers an alternative way to implement security in on-demand
Automated Time Manager: Effectiveness of Self-Regulation on Time Management Through a Smartphone Application

We investigated the effectiveness of a self-regulation strategy on time management leveraged by smartphone capabilities using a theoretical framework of self-regulation that consists of four elements: 1) goal setting; 2) task strategy utilization; 3) self-monitoring and reflection; and 4) self-efficacy and intrinsic motivation. We determined the goals and strategies adopted during college life by surveying 295 college students and identified time management as a fundamental element for achieving such goals and strategies. To improve students’ time management, we developed a smartphone application, automated time manager (ATM), designed to provide users with visualizations of their physical activities and phone usage reports and also to acquire smartphone sensor and usage data. From a field study of 46 college students, we highlighted three primary user experiences—awareness of unawareness, preferred feedback, and contextual but obvious use—and an overall positive time management outcome with ATM. We present an empirical study that transforms self-regulation, a well-known approach in social sciences, into computing and discusses the salient design implications for supporting time management in a more effective manner with a smartphone application.
Investigating various many-body force fields for their ability to predict reduction in elastic modulus due to vacancies using molecular dynamics simulations

ABSTRACT Molecular dynamics simulations are more frequently being utilised to predict macroscale mechanical properties as a result of atomistic defects. However, the interatomic force field can significantly affect the resulting mechanical properties. While several studies exist which demonstrate the ability of various force fields to predict mechanical properties, the investigation into which is most accurate for the investigation of vacancies is limited. To obtain meaningful predictions of mechanical properties, a clear understanding of force field parameterisation is required. As such, the current study evaluates various many-body force fields to demonstrate the reduction in mechanical properties of iron and iron–chromium due to the presence of vacancies while undergoing room temperature atomistic uniaxial tension. Reduction was normalised in each case with the zero-vacancy elastic modulus, removing the need to predict an accurate nominal elastic modulus. Comparisons were made to experimental data and an empirical model from literature. It was demonstrated that accurate fitting to vacancy formation and migration energy allowed for accurate predictions. In addition, bond-order based force fields showed enhanced predictions regardless of fitting procedure. Overall, these findings highlight the need to understand capabilities and limitations of available force fields, as well as the need for enhanced parameterisation of force fields.
Communicative emergence and cultural evolution of word meanings

The question of how language evolved has received an increasing amount of attention in recent years. Compared to seemingly more complex phenomena such as syntax, word meanings are usually seen as relatively easy to explain. Mainstream accounts in psycholinguistics and evolutionary linguistics assume that word meanings correspond to stable concepts which are prior to language and derive straightforwardly from human perception of structure in the world. Taking a cognitive linguistic approach based on psycholinguistic evidence, I argue instead that word meanings are conventions, grounded, learned and used in the context of communication. The meaning of a word is the sum of its contexts of use, with particular features of these contexts made more or less salient by mechanisms of attentional learning and communicative inference. Evolutionarily, word meanings arise as an emergent product of humans’ adapted tendency to infer each other’s intentions using contextual cues. They are then shaped over cultural evolution by the need to be learnable and useful for communication. This thesis presents a series of experiments that test the effect of these pressures on the origins and development of word meanings. Experiment 1 investigates the origins of strong tendencies for words to specify features on particular dimensions (such as the shape bias). The results show that these tendencies arise via attentional learning effects amplified by iterated learning. Dimensions which are less salient in contexts of learning and use drop out of word meanings as they are passed down a chain of learners. Experiments 2, 3 and 4 investigate the structure of word meanings produced during either paired communication games or individual labelling of images by similarity. While communication alone leads to word meanings that are unstructured and poorly aligned within pairs, communication plus iterated learning leads to word meanings that increase in structure and alignment over generations. Finally, Experiment 5 investigates the interaction of event structure and developing conventions in shaping word meanings. The structure of events in an artificial world is shown to influence lexicalisation patterns in the languages conventionalised by communicating pairs. Event features that are less predictable across communicative contexts tend to be more strongly associated with the conventions in the language. Overall, the experiments show that rather than straightforwardly reflecting pre-linguistic conceptualisation, word meanings are also dynamically shaped by learning and communication. In addition, these processes are constrained by the conventions that already exist within a language. This illuminates the mixture of convergence and diversity we see in word meanings in natural languages, and gives insight into their evolutionary origins.
A Survey on Detecting Brain TumorinmriImages Using Image Processing Techniques

Medical Image Processing is the fast growing and challenging field now a days. Medical Image techniques are used for Medical diagnosis. Brain tumor is a serious life threatening disease. Detecting Brain tumor using Image Processing techniques involves four stages namely Image Pre-Processing, Image segmentation, Feature Extraction, and Classification. Image processing and neural network techniques are used to improve the performance of detecting and classifying brain tumor in MRI images. In this survey various Image processing techniques are reviewed particularly for Brain tumor detection in magnetic resonance imaging. More than twenty five research papers of image processing techniques are clearly reviewed.
Determinants of Agroecological Practices Adoption in the Sudano-Sahelian Zone

Under the combined effect of both climatic and anthropogenic factors, agroecosystems and especially arable soils undergo a worrying and fast degradation in the Sudano-Sahelian zone of Western Africa threatening its socio-economic development. Food systems need to be better managed to be more resilient, to increase agricultural production, while conserving natural resources and biodiversity. Agroecological practices alternatively with traditional cultural techniques have been locally experimented to cope with local pedoclimatic constraints such as weak (low) soil fertility and climate change, increasing food demand and economic conditions. Our work aims at by taking stock of agroecological knowledge as well as the determinants of their adoption with small-scale farmers in Eastern Burkina Faso. A survey (48 farmers) was conducted in Sampieri (Kantchari district), and Logit model was used to determine equations for agroecological practices adoption. Results show that traditional production practices for millet-bean cultural systems are gradually being replaced by those of agroecological. In fact, 60.4% of producers have participated in at least one agroecological training session and 60.8% of producers are interested at least in one agroecological topic. The most adopted and practiced techniques were superficial plowing, stone-rows, zai and compost, single or in combination (60% of the producers). Determinants of these practices adoption were the increased crop yields, improved of producers’ incomes, the provision or otherwise of material and human resources and training. Additionally, variables such as training, possession of agricultural equipment were positively correlated to the adoption of agroecological practices while illiteracy impacts negatively and significantly this adoption. Moreover, agroecological practices had a significant effect on grain and straw yields of sorghum, thus confirming producers’ claims about the improvements in production observed following the adoption of these practices.
Examining conservation agriculture soil profiles: Outcomes from northeastern Italian silty soils combining indirect geophysical and direct assessment methods

Conservation agriculture (CA) is an agronomic system, including no‐tillage, cover crops and residue retention on the soil surface, which represents more sustainable management compared to conventional ploughing systems (CV). Conservation agriculture is widespread in some parts of the world (i.e. South America and the USA), whereas it is still developing in others (i.e. Europe). One of the main reasons for the slow European uptake of CA is low yield because of the worsening of soil physical quality, in particular increased compaction and reduced hydraulic permeability. The effects of CA on soil physical dynamics are poorly documented, particularly during the transition phase between CV and CA and for fine‐textured soils. Therefore, in this study, the effects of CA on soil volumetric water content, bulk density, penetration resistance and electrical resistivity are presented over a 3‐year monitoring period. The experiment was established in 2010 on four farms in the Veneto region (northeastern Italy) with silty soils, where CA practice was compared with CV. The dynamics of soil physical properties were monitored from 2014 to 2016 following a 3‐year crop rotation cycle. Every year, bulk density analysis, a penetration resistance test and three‐dimensional electrical resistivity tomography were performed. The results showed that soil physical properties clustered depending on soil texture: in silty loam soils any specific improvements were highlighted after 6 years of CA, whereas in loamy soils soil compaction was observed in both CA and CV. Indeed, CA resulted in soil compaction below a depth of 10 cm (+107% of degree of compaction), whereas CV resulted in the formation of a plough pan in the 35–55‐cm layer (+111% of degree of compaction). The low soil organic carbon and low clay contents made loamy soil particularly prone to compaction, highlighting the influence of fine texture on soil structure evolution during the transition phase.
Undergraduate Students’ Solutions of Modeling Problems in Algorithmic Graph Theory

Graphs can be considered as useful mathematical models. Graph algorithms are a common part of undergraduate courses in discrete mathematics. Even though they have been successfully implemented in secondary curricula, little research has been dedicated to the analysis of students’ work. Within a discrete mathematics course for university students, several graph algorithms were introduced via their applications. At the end of the course, the students took a test focused, inter alia, on applications of the algorithms. The mistakes that occurred in 127 students’ solutions of three problems (the Chinese postman problem, the shortest path problem, and the minimum spanning tree problem) were categorized and compared. Surprisingly, no mistakes were identified in the mathematization of situations or in the interpretation of results with respect to the wording of the problem. The categories of errors varied regardless of the problem types. Hierarchical cluster analysis grouped together the students’ solutions for the Chinese postman problem and the minimum spanning tree problem. By means of nonparametric item response theory analysis, the Chinese postman problem was identified as the most problematic for students. Possible sources of this difficulty are discussed in more detail herein.
Localization and Clustering Based on Swarm Intelligence in UAV Networks for Emergency Communications

In recent years, unmanned aerial vehicle (UAV) networks have been a focus area of the academic and industrial research community. They have been used in many military and civilian applications. Emergency communication is one of the essential requirements for first responders and victims in the aftermath of natural disasters. In such scenarios, UAVs may configure ad hoc wireless networks to cover a large area. In UAV networks, however, localization and routing are challenging tasks owing to the high mobility, unstable links, dynamic topology, and limited energy of UAVs. Here, we propose swarm-intelligence-based localization (SIL) and clustering schemes in UAV networks for emergency communications. First, we propose a new 3-D SIL algorithm based on particle swarm optimization (PSO) that exploits the particle search space in a limited boundary by using the bounding box method. In the 3-D search space, anchor UAV nodes are randomly distributed and the SIL algorithm measures the distance to existing anchor nodes for estimating the location of the target UAV nodes. Convergence time and localization accuracy are improved with lower computational cost. Second, we propose an energy-efficient swarm-intelligence-based clustering (SIC) algorithm based on PSO, in which the particle fitness function is exploited for intercluster distance, intracluster distance, residual energy, and geographic location. For energy-efficient clustering, cluster heads are selected based on improved particle optimization. The proposed SIC outperforms five typical routing protocols regarding packet delivery ratio, average end-to-end delay, and routing overhead. Moreover, SIC consumes less energy and prolongs network lifetime.
PENGARUH MODEL PEMBELAJARAN CREATIVE PROBLEM SOLVING BERBANTUAN MEDIA MAPLE 11 TERHADAP KEMAMPUAN PEMECAHAN MASALAH MATEMATIS

Rendahnya kemampuan pemecahan masalah matematis peserta didik di MAN 2 Bandar Lampung disebabkan karena peserta didik kesulitan dalam menyelesaikan soal-soal matematika dan peserta didik jarang sekali mengajukan pertanyaan atau mengemukakan ide pengerjaannya. Penelitian ini bertujuan untuk mengetahui pengaruh kemampuan pemecahan masalah matematis peserta didik yang mengikuti pembelajaran dengan menggunakan model pembelajaran Creative Problem Solving dengan peserta didik yang mengikuti model pembelajaran Creative Problem Solving yang berbantuan media Maple 11 maupun peserta didik yang mengikuti metode pembelajaran konvensional yang dilakukan oleh peneliti pada peserta didik kelas XI di MAN 2 Bandar Lampung. Penelitian ini merupakan penelitian kuantitatif jenis eksperimen dengan Quasy Experimental Design . Dalam penelitian ini jumlah populasi sebanyak 121 peserta didik dengan teknik Sampling dalam penelitian ini menggunakan sampel jenuh. Berdasarkan hasil perhitungan, setelah dilakukan uji hipotesis menggunakan uji ANAVA didapat F observasi sebesar 10,54. Apabila nilai F observasi tersebut dibandingkan dengan nilai F tabel sebesar 3,07, maka dapat disimpulkan bahwa F observasi ≥ F tabel, dengan demikian hipotesis H 0 ditolak dan H 1 diterima, yang berarti bahwa terdapat pengaruh pembelajaran CPS berbantuan Maple 11 terhadap kemampuan pemecahan masalah peserta didik.